WO2018137331A1 - 数据处理方法、装置、设备及计算机可读存储介质 - Google Patents

数据处理方法、装置、设备及计算机可读存储介质 Download PDF

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Publication number
WO2018137331A1
WO2018137331A1 PCT/CN2017/096001 CN2017096001W WO2018137331A1 WO 2018137331 A1 WO2018137331 A1 WO 2018137331A1 CN 2017096001 W CN2017096001 W CN 2017096001W WO 2018137331 A1 WO2018137331 A1 WO 2018137331A1
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Prior art keywords
delivery
order
unallocated
order group
group
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PCT/CN2017/096001
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English (en)
French (fr)
Inventor
黄绍建
徐明泉
王从宇
叶发达
陈进清
咸珂
杨秋源
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北京小度信息科技有限公司
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Publication of WO2018137331A1 publication Critical patent/WO2018137331A1/zh
Priority to US16/520,021 priority Critical patent/US20190347753A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • G06Q10/063114—Status monitoring or status determination for a person or group
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • G06Q10/063116—Schedule adjustment for a person or group
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping

Definitions

  • the embodiments of the present disclosure relate to the field of computer application technologies, and in particular, to a data processing method, apparatus, device, and computer readable storage medium.
  • the delivery personnel are required to participate in the completion, and the delivery personnel complete the operations of picking up and/or dispatching according to the delivery order. Since the distribution requirements of different distribution services may be different, the delivery scheduling method is also different, which results in the current distribution business using separate delivery personnel for distribution scheduling, which undoubtedly increases the distribution cost and leads to distribution resources. Waste.
  • the current distribution business uses separate delivery personnel for distribution scheduling, and the inventors found in the research that various distribution services are usually configured according to the maximum delivery pressure in order to ensure the quality of service.
  • the delivery personnel are very redundant in some cases, resulting in waste of distribution resources, and most of the current delivery service delivery scheduling methods are usually performed manually, using manual sorting and delivery orders for delivery scheduling, and delivery personnel.
  • the experience is high, there is a problem of misclassification, and it will affect the efficiency of distribution.
  • an embodiment of the present disclosure provides a data processing method, apparatus, device, and computer readable storage medium, which are used to reduce distribution cost, improve utilization of distribution resources, and ensure distribution efficiency.
  • a first aspect of an embodiment of the present disclosure provides a data processing method, including:
  • the assigning the unallocated order group to the matching delivery personnel based on the delivery indicator and the status indicator includes:
  • the unallocated order group is assigned to the matching delivery person in response to the determination result that the distribution order group satisfies the scheduling condition.
  • the method further includes:
  • An unallocated order group similar to the assigned order group for each shipping person is added to the assigned order group based on the distance between the starting point addresses and the distance between the ending addresses.
  • the at least two distribution services include a first delivery service and a second delivery service.
  • the at least two distribution services include a first delivery service and a second delivery service
  • the delivery type of the first delivery service includes a delivery type that extracts the delivery object from the collection point and delivers to the recipient, and a pickup type that extracts the delivery object from the sender and delivers the delivery object to the collection point;
  • the delivery type of the second delivery service is to receive the delivery object from the sender and deliver it to the recipient.
  • obtaining an unallocated order group of the first delivery service including:
  • obtaining an unallocated order group of the second delivery service including:
  • a delivery order in which the distance between the starting point addresses is within a first distance range, the distance between the end point addresses is within a second distance range, and the time difference between the desired completion times is within a preset time range is divided into the same
  • the order group is not assigned.
  • the delivery indicator includes a start address, an end address, and a desired completion time
  • Determining a delivery indicator for each unallocated order group of the first delivery service including:
  • the starting address of the first delivery order is used as the starting address of each unallocated order group, and the collection point address is used as the ending address of each unallocated order group;
  • the collection point address is used as the starting address of each unallocated order group, and the destination address of the last delivered delivery order is used as the end address of each unallocated order group;
  • Determining a delivery indicator for each unallocated order group of the second delivery service including:
  • the expected delivery order of each delivery person is planned for each delivery order
  • the status indicator of each of the delivery personnel includes an estimated delivery time and an estimated delivery location
  • Each of the unallocated order groups is assigned to a matching delivery person based on the matching score.
  • the assigning the unallocated order group to the matching delivery personnel based on the delivery indicator and the status indicator includes:
  • N is the total number of unallocated order groups, an integer greater than or equal to 1
  • M is an integer greater than or equal to 1
  • Each of the unallocated order groups is assigned to the corresponding delivery person according to the distribution list with the highest list score.
  • determining the estimated delivery time of the delivery personnel and the estimated delivery location including:
  • the estimated completion time of the allocated order group is used as the estimated delivery time and the destination address of the allocated order group as the estimated delivery location according to the allocated order group whose delivery personnel are not currently delivered.
  • the estimated completion time of each unassigned order group for each delivery personnel delivery is determined as follows:
  • the method further includes:
  • the order completion time of each of the delivery orders is sent to the sender terminal or the recipient terminal corresponding to each delivery order.
  • the method further includes:
  • the unallocated order group of the first delivery service and/or the undistributed delivery order of the second delivery service with an order similarity greater than a similar threshold are added to the allocated order group.
  • a second aspect of the embodiments of the present disclosure provides a data processing apparatus, including:
  • An order obtaining module configured to respectively obtain an unallocated order group that is not allocated by at least two types of distribution services
  • a first indicator determining module for determining a status indicator of the delivery personnel
  • a second indicator determining module configured to determine a delivery indicator of the unallocated order group
  • a first order allocation module configured to allocate the unallocated order group to a matching delivery person based on the delivery indicator and the status indicator.
  • the first order allocation module includes:
  • An order determining unit configured to determine a delivery person that matches the unallocated order group based on the delivery indicator and the status indicator;
  • An order allocation unit configured to assign any of the unallocated order groups to the matching delivery personnel in response to the determination result that any of the unallocated order groups meet the scheduling condition.
  • the device further includes:
  • a second order allocation module for using the distance between the starting address and the destination address The distance between the unallocated order groups that are similar to the assigned order group of any of the delivery personnel is added to the assigned order group.
  • the at least two distribution services include a first delivery service and a second delivery service.
  • the at least two types of distribution services include a first delivery service and a second delivery service; a delivery period of the first delivery service is greater than a delivery period of the second delivery service; and the first delivery service is The distribution peak period of the second distribution service is different;
  • the delivery type of the first delivery service includes a delivery type that extracts the delivery object from the collection point and delivers to the recipient, and a pickup type that extracts the delivery object from the sender and delivers the delivery object to the collection point;
  • the delivery type of the second delivery service is to receive the delivery object from the sender and deliver it to the recipient.
  • the device further includes:
  • a first order dividing module configured to select a cluster center order according to a distance between the ungrouped delivery order and the collection point address in the first delivery service
  • the device further includes:
  • a second order dividing module configured to determine a starting address, an ending address, and a desired completion time of the delivery order that is not allocated by the second delivery service
  • a delivery order in which the distance between the starting point addresses is within a first distance range, the distance between the end point addresses is within a second distance range, and the time difference between the desired completion times is within a preset time range is divided into the same
  • the order group is not assigned.
  • the delivery indicator includes a start address, an end address, and a desired completion time
  • the first indicator determining module includes:
  • a first determining unit configured, for each unallocated order group of the first delivery service, an earliest expected completion time of each delivery order in each unallocated order group as the unallocated order group Expected completion time; plan the expected delivery order of each delivery order according to the user address of each delivery order of each unallocated order group and the collection point address; For the pickup type, the starting address of the first delivery order is used as the starting address of each unallocated order group, and the collection point address is used as the ending address of each unallocated order group; a piece type, the collection point address is used as a starting address of each unallocated order group, and an end address of a last delivered delivery order is used as an end address of each unallocated order group;
  • a second determining unit configured, for each unallocated order group of the second delivery service, an earliest expected completion time of each delivery order in each unallocated order group as corresponding to each unallocated order group
  • the expected completion time of each delivery personnel according to the starting address, the destination address of each delivery order of each unallocated order group, and the estimated delivery position of each delivery person, the planned delivery of each delivery order is planned for each delivery person.
  • the starting point address of the first delivery delivery order is used as the starting address of each of the undelivered order groups corresponding to each of the delivery personnel, and the destination address of the last delivered delivery order as each of the unallocated The destination address of the order group for each of the delivery personnel.
  • the status indicator of the delivery personnel includes an estimated delivery time and an estimated delivery location
  • the first order allocation module includes:
  • a first calculating unit configured to: according to the distance between the estimated delivery location of each delivery person and the starting address of each unallocated order group, the estimated delivery time, and the expected delivery of each unallocated order group Time difference of time, familiarity with the start address of each unallocated order group, familiarity with the end address of each unallocated order group, estimated completion time of each unallocated order group for delivery completion, each of said Calculating a matching score of each unallocated order group and each of the delivery personnel by one or more factors in the urgency of the unallocated order group;
  • a first order allocation unit configured to allocate each of the unallocated order groups to the matching delivery personnel according to the matching score.
  • the first order allocation unit is specifically configured to: use each unallocated order group as the Nth unallocated order group to be determined, perform undetermined delivery personnel, determine and undetermined each The operation of the delivery personnel with the highest matching degree of the unallocated order group obtains M allocation lists; wherein N is the total number of unallocated order groups, which is greater than or equal to 1 Number; M is an integer greater than or equal to 1;
  • Each unallocated order group is assigned to a corresponding delivery person according to an allocation list with an optimal list score.
  • the second indicator determining module is specifically configured to:
  • the estimated completion time of the allocated order group is used as the estimated delivery time and the destination address of the allocated order group as the estimated delivery location according to the allocated order group whose delivery personnel are not currently delivered.
  • the device further includes:
  • a first time determining module configured to determine, according to a delivery path of each unallocated order group, an action speed of each of the delivery personnel, and a user waiting time of each delivery order in each unallocated order group The delivery personnel are expected to complete the order completion time for each delivery order;
  • a second time determining module configured to calculate, according to the order completion time, an estimated completion time of each of the unallocated order groups that each of the delivery personnel is expected to complete.
  • the device further includes:
  • the third time determining module determines, for each allocated order group, an order completion time for which the delivery personnel matching the delivery is expected to complete each of the delivery orders;
  • the time prompting module is configured to send an order completion time of each of the delivery orders to a sender terminal or a receiver terminal corresponding to each delivery order.
  • the device further includes:
  • a similarity calculation module configured to calculate an allocated order group of each delivery person and an unallocated order group of the first delivery service and the second delivery based on a distance between the start address and a distance between the end addresses The order similarity of the unallocated delivery order of the business;
  • a third order allocation module configured to add an unallocated order group of the first delivery service with an order similarity greater than a similar threshold and/or a delivery order that is not allocated by the second delivery service to the allocated order group .
  • a third aspect of an embodiment of the present disclosure provides a data processing device including a processing component And storage components;
  • the storage component is for storing one or more computer instructions, wherein the one or more computer instructions are executed by the processing component to:
  • Each of the unallocated order groups is assigned to a matching delivery person based on the delivery metrics and the status metrics.
  • a fourth aspect of an embodiment of the present disclosure provides a computer readable storage medium having stored thereon computer instructions that, when executed by a processor, implement the following steps:
  • the fusion scheduling of the delivery orders of the at least two distribution services is realized, so that at least two distribution services can share the same batch of delivery personnel, thereby reducing the distribution cost and making the distribution resources fully utilized, thereby avoiding The distribution resources are wasted, and the automatic delivery scheduling of the delivery orders is realized, and no manual sorting is required, which ensures the distribution efficiency.
  • FIG. 1 is a schematic flowchart diagram of a data processing method according to an exemplary embodiment of the present disclosure
  • FIG. 2 is a schematic flowchart diagram of a data processing method according to an exemplary embodiment of the present disclosure
  • FIG. 3 is a schematic structural diagram of a data processing apparatus according to an exemplary embodiment of the present disclosure
  • FIG. 4 is a schematic structural diagram of a data processing apparatus according to an exemplary embodiment of the present disclosure.
  • FIG. 5 is a schematic structural diagram of a data processing device according to an exemplary embodiment of the present disclosure.
  • the distribution service for providing logistics services is more and more diversified.
  • different distribution services usually use separate delivery personnel for distribution scheduling, taking the two common distribution services as an example.
  • the delivery type of the first delivery service includes a pickup type and a delivery type, and the pickup type refers to extracting the delivery object from the sender and sending To reach the collection point, the dispatch type refers to extracting the delivery object from the collection point and delivering it to the recipient. Therefore, the delivery order of the first delivery service may be a pickup order or a dispatch order, and the delivery operation of the first delivery service may be Pickup operation or dispatch operation.
  • the ordinary express delivery service is a typical landing service.
  • the delivery objects obtained from the sender are sent to the collection point for delivery, and for the delivery type, the delivery objects are extracted from the collection point for delivery to the recipient.
  • the delivery object may be, for example, a variety of items, and may specifically be an item obtained based on an online transaction.
  • the delivery type of the second delivery service refers to receiving the delivery object from the sender and delivering it to the recipient, which may be delivered according to the expected completion time, and the delivery operation of the second delivery service includes the pickup operation and the dispatch operation, in practical application.
  • a take-out delivery such as an O2O (Online To Offline) take-out application, it is a typical application of the second distribution service.
  • the peak delivery period of the floor distribution distribution service may be, for example, 8-day.
  • the pick-up period may be, for example, 7-9 o'clock every day, while the peak delivery period of the take-away delivery service may be, for example, at the peak of meals at 11-13 and 17-19.
  • the above two types of distribution services have a large manpower waste in the low peak period of each distribution, which is also a major cause of high distribution costs.
  • the delivery peak period may be different except for different distribution services, and the requirements for delivery timeliness may be different, such as the first delivery service and the second.
  • the delivery period of the delivery service is different, and the delivery deadline of the delivery order of the first delivery service is greater than the delivery deadline of the delivery order of the second delivery service;
  • the delivery period may be the length of time from the delivery order generation time to the delivery order delivery completion time, and the delivery deadline of the delivery order of the first delivery service is greater than the delivery deadline of the delivery order of the second delivery service, that is, the indication
  • the delivery timeliness of a distribution service is lower than the delivery timeliness of the second delivery service.
  • the first delivery service may complete the delivery order within 24 hours from the start of the order generation time, and the second delivery service may need to receive the order.
  • the fulfillment order is completed within half an hour after the start of the generation time. So if it will be different
  • the distribution orders of the distribution business are integrated and dispatched, and the same batch of delivery personnel can be used to distribute peaks to each other, thereby reducing the number of delivery personnel and achieving cost saving. Based on this consideration, the exemplary embodiments of the present disclosure provide a data processing method, apparatus, processing device, and computer readable storage medium to achieve how to integrate scheduling, achieve cost saving, and improve utilization of distribution resources.
  • FIG. 1 is a flowchart of a data processing method according to an exemplary embodiment of the present disclosure, and the method may include the following steps:
  • an unallocated order group for each type of distribution service is obtained by grouping unallocated delivery orders.
  • Each distribution service includes one or more unallocated order groups.
  • the delivery scheduling can be performed for the delivery orders of two or more different delivery services.
  • the unallocated order group includes at least one delivery order.
  • a distribution order of a distribution service may include a lot, and in order to optimize the scheduling effect and ensure the distribution efficiency, the inventors have found that the delivery orders of each distribution service can be grouped so that each is not The start address of each delivery order in the assigned order group is close, the end address is close, and/or the expected completion time is close.
  • the distances of the start addresses of the respective delivery orders in the same unallocated order group are within a first distance range
  • the distances between the end point addresses are within a second distance range
  • the desired completion time is between each other.
  • the time difference is within the preset time range.
  • the expected completion time of the delivery order may refer to the expected delivery time of the delivery object to the recipient or the expectation of receiving the delivery object from the sender.
  • Receiving time; for the second delivery service, the expected completion time of the delivery order may refer to the expected delivery time of the delivery object to the recipient.
  • the expected completion time of the delivery order may be a specific time, for example, 8:40; it may be provided by the user, or the system may be set according to historical rules, such as for the first delivery service, due to the timeliness of delivery Not high, can be delivered within the delivery period, so the expected completion time can be set to any time within the delivery period; for the second delivery service, because the delivery timeliness requirements are higher, the expected completion time can be based on the delivery order
  • the generation time and the maximum delivery time of the delivery object are determined, and the maximum delivery time can be calculated based on the farthest distance between the recipient and the sender, the minimum speed of the delivery person, and the like.
  • each unallocated order group may include only one delivery order, that is, the delivery orders for different delivery services need not be grouped, and the fusion scheduling may be directly performed by using the technical solution of the present disclosure.
  • the status indicator may include at least an estimated delivery location.
  • the estimated delivery location may be the location of the person at the time the delivery person is able to deliver.
  • the status indicator may also include an estimated delivery time, which is the time at which the delivery personnel can deliver, such as 8:00.
  • the delivery location is expected to be the current location of the delivery personnel, and the estimated delivery time is the current time. If there is a delivery order that has not been delivered, the estimated delivery time is the time when the last delivery order is delivered.
  • the estimated delivery location is the location of the person who completed the delivery of the last delivery order, which will be described in detail in the following examples.
  • the delivery indicator may include at least a starting address.
  • each fulfillment order will have a starting address and a destination address.
  • the starting address is the sender address
  • the destination address is the collection point address.
  • the starting address is the collection point address and the destination address is the recipient address.
  • the starting address and the ending address are all the collection point addresses; for example, for the second delivery service, the starting address This is the sender address, and the destination address is the recipient address.
  • the starting address of the unassigned order group may be the starting address of the first delivery order in the unallocated order group.
  • the delivery indicator may further include a desired completion time, for example, the earliest expected completion time of each delivery order in each unallocated order group may be used as the expectation of each unallocated order group. Complete time.
  • the delivery indicator may further include an end address.
  • the destination address of an unassigned order group may be the destination address of the delivery order that is expected to be the last delivery in the unallocated order group.
  • each unallocated order group can be assigned to a matching delivery person according to the distance between the starting address of each unallocated order group and the estimated delivery location of each delivery person, and the closer the distance is, the unallocated The higher the match between the order group and the delivery staff.
  • only one unallocated order group can be assigned to each delivery person within the current delivery scheduling period.
  • the distribution cost can be greatly reduced, the distribution workload can be balanced, and the distribution orders can be found according to the distribution indicators and the status indicators.
  • the delivery staff realizes automatic scheduling and eliminates the need for manual sorting, maximizing the distribution efficiency.
  • at least two kinds of distribution services include the first delivery service and the second delivery service, since the peak delivery period is different, the delivery workload of different time periods can be supplemented each other, and the delivery pressure is balanced.
  • a matching score of each unallocated order group and each delivery personnel may be calculated; thereby, according to the matching score, each unallocated order group may be allocated to match Delivery staff.
  • each of the undivided points may be adopted by using a global optimal solution
  • the assigned order group is assigned to the matching delivery person.
  • the step of assigning according to the matching score may specifically include:
  • Each unallocated order group is respectively used as the Nth unallocated order group to be determined, and the unmatched delivery personnel are executed to determine the operation of the delivery personnel with the highest degree of matching with each unallocated order group.
  • M allocation lists where N is the total number of unallocated order groups, an integer greater than or equal to 1; M is an integer greater than or equal to 1; M ⁇ N*(N-1)*(N-2)*-2 *1;
  • the unallocated order group is assigned to the corresponding delivery person according to the distribution list with the best score of the list.
  • the matching scores of each unallocated order group and the three delivery personnel can be calculated, assuming that the matching scores of A and X are P AX , the matching scores of A and Y are P AY , and the matching scores of A and Z are P AZ;
  • the matching score of B and X is P BX , the matching score of B and Y is P BY , and the matching score of B and Z is P BZ ;
  • A selects the one with the highest matching degree from X, Y, and Z according to the matching scores P AX , P AY , P AZ , and assumes that the highest matching degree is P AX .
  • X; B is the second unallocated order group to be determined. Since A has selected X, B selects the one with the highest matching degree from the unmatched Y and Z, and assumes that the highest matching degree is P BZ.
  • Z the allocation list obtained at this time is: A is assigned to X; B is assigned to Z; the sum of matching scores of P AX and P BZ is calculated, assuming R1, which can be used as a list score of the allocation list;
  • A is the second unallocated order group to be determined
  • B is the first unallocated order group to be determined, assuming that the obtained allocation list is assigned to A by A;
  • B is assigned to X;
  • the sum of the matching scores of P BZ assuming R2, can be used as the category score of the allocation list;
  • A when A is the first unallocated order group to be determined, A is preferred. From X, Y, and Z, the delivery personnel X with the highest matching degree are selected, and B is the second unallocated order group to be determined. Only the delivery personnel with the highest matching degree can be selected from Y and Z, and B is the first. For an unallocated order group to be determined, the delivery personnel with the highest matching degree can be preferentially selected from X, Y, and Z as X, and A can only select the highest matching delivery personnel from Y and Z, so A When B and B are respectively the Nth unallocated order group to be determined, the resulting allocation list may not be the same.
  • R2 By comparing R1 and R2, it is possible to determine an allocation list with the best list score. If R2 is optimal, it is allocated according to the allocation list corresponding to R2, that is, A is assigned to Y; B is assigned to X.
  • the matching score is larger, indicating that the matching degree is higher, the larger the list score, the better the list score; otherwise, if the matching score is smaller, indicating that the matching degree is higher, the smaller the list score, indicating that the list score is more excellent.
  • each distribution person is only assigned one unallocated order group, If there are remaining unallocated order groups to be allocated, then return to step 101 to continue execution.
  • the unallocated order group that obtains at least two delivery services respectively may include:
  • An unallocated order group of the at least two types of delivery services is obtained separately for each preset scheduling time. That is, the distribution scheduling is performed periodically to ensure the scheduling accuracy and ensure the distribution efficiency.
  • delivery scheduling can also be performed in real time.
  • an unassigned mark label can be set for the unallocated order group, and the order group with the unassigned mark symbol is an unallocated order group, which can be based on the unallocated mark symbol.
  • assigning the unallocated order group to the matching delivery personnel based on the delivery indicator and the status indicator may include:
  • the unallocated in response to a determination result that the unallocated order group satisfies a scheduling condition
  • the order group is assigned to the matching delivery person.
  • the scheduling condition may be that the allocated order group of the delivery personnel that matches the unallocated order group is completed. That is, after the distribution of the assigned order group of the delivery personnel matching any unallocated order group is completed, the unallocated order group is assigned to the matching delivery personnel.
  • the scheduling condition may be that the time difference between the expected completion time and the current time of the unallocated order group is less than a preset value, that is, the current time is close to the expected completion time. That is, when the time difference between the expected completion time of the unallocated order group and the current time is less than the preset value, then any unallocated order group is assigned to the matching delivery personnel.
  • the step of returning the unallocated order group that respectively obtains at least two types of delivery services is performed to continue the delivery scheduling.
  • the method may further include:
  • An unallocated order group similar to the assigned order group of any of the delivery personnel is added to the allocated order group based on the distance between the starting point addresses and the distance between the destination addresses. Thereby, the delivery can be realized, and the delivery time and distribution efficiency can be ensured.
  • An assigned order group is also an unallocated order group that has been assigned to a delivery person.
  • any of the unallocated order groups are added to the allocated order group, so that the delivery personnel can perform the delivery.
  • the order similarity between the allocated order group of any delivery person and each unallocated order group may be calculated according to the distance between the starting address and the distance between the end addresses;
  • different scores may be preset according to different distance ranges, so that the distance between the assigned order group and the start address of any unallocated order group and the distance between the destination addresses are determined, respectively,
  • the distance corresponding to the distance range is the first similarity score
  • the distance between the end addresses corresponds to the distance range
  • the second similarity score the first similarity score and the second similarity score are added or weighted. Average or weighted summation, etc., can be calculated to obtain order similarity.
  • the unallocated order group may have a desired completion time
  • a third similarity score may be calculated according to the time difference between the unallocated order group and the expected completion time of the allocated order group, for example, a score corresponding to a different time value range may be preset. The score corresponding to the time range of the time difference is found as the third similarity score.
  • the first similarity score, the second similarity score, and the third similarity score are added or weighted average or weighted and the like, and the order similarity is obtained.
  • an unallocated order group having an order similarity greater than a similar threshold can be added to the assigned order group of each of the delivery personnel.
  • the delivery metrics of the unallocated order group may include a starting address, an ending address, and/or a desired completion time.
  • the start or end address can be determined in conjunction with the expected delivery order for each fulfillment order in the unallocated order group.
  • the way in which the delivery order of different distribution services is determined is also different.
  • the at least two distribution services may include a first delivery service and a second delivery service
  • the determining step of the first delivery service delivery indicator may include:
  • the earliest expected completion time of each delivery order in each unallocated order group is taken as the expected completion time of each unallocated order group; according to the user address and the collection point address of each delivery order of each unallocated order group, planning The expected delivery order for each delivery order;
  • the starting address of the first delivery order is used as the starting address of each unallocated order group, and the collection point address is used as the ending address of each unallocated order group;
  • the collection point address is used as the starting address of each unallocated order group, and the destination address of the last delivered delivery order is used as the end address of each unallocated order group;
  • the planned delivery order of each delivery order can be scheduled according to the minimum path principle, so that the delivery path is the shortest.
  • the minimum path principle is based on the principle that the total path is the smallest, and the corresponding delivery path is planned, so that the order of delivery can be determined.
  • the determining step of the second delivery service delivery indicator may include:
  • the planned delivery order of each delivery person is planned for each delivery order
  • the delivery indicators of the same unallocated order group corresponding to different delivery personnel may be different.
  • the expected delivery sequence includes a pickup order and a dispatch order
  • the order of picking up is obtained according to the starting address of each delivery order and the estimated delivery location plan of each delivery personnel, and the order of dispatching is obtained according to the destination address of each delivery order and the starting address of the last delivery order of the pickup.
  • the starting address of the delivery order of the first pickup is used as the starting address of each of the undistributed order groups corresponding to each of the delivery personnel, and the destination address of the delivery order of the last dispatch is used as the each The unallocated order group corresponds to the destination address of each of the delivery personnel.
  • the completion time requirement is high.
  • delivery is expected, so the order of picking up each delivery order in each unallocated order group can be planned according to the pickup waiting time and according to the minimum path principle, so that the pickup path is the shortest when the pickup waiting time is the shortest.
  • the dispatch order may be planned according to the minimum completion path according to the expected completion time, so that the dispatch path is the shortest when the delivery completion time of the unallocated order group is less than or equal to the expected completion time.
  • the estimated completion time for each distribution staff to complete each unallocated order group can be determined as follows:
  • the order completion time for each delivery person to complete each delivery order; the order completion time Can be a specific moment, such as 15:30.
  • the delivery path of each unallocated order group may be re-determined to ensure that the estimated completion time is less than or equal to the expected completion time and the delivery path is shorter.
  • the delivery path is composed of a pickup path and a dispatch path
  • the user waiting time may include the pickup waiting time of the sender and the dispatch waiting time of the receiver.
  • the user waiting time may include the pickup waiting time of the sending party
  • the user waiting time may include the pickup waiting time at the collection point and the dispatch waiting time at the receiving party.
  • the estimated completion time of the unallocated order group and the order of each delivery order in the unallocated order group are calculated.
  • Completion time; for the second delivery service when determining the delivery indicator of the unallocated order group of the second delivery service, the estimated completion time of each undelivered order group corresponding to each delivery personnel and each delivery order corresponding to each The order completion time of the delivery staff.
  • the first delivery service can also be pre-assigned The order completion time is calculated in a single group, so that after the unallocated order group is assigned to the delivery person, the order completion time can be directly utilized.
  • the status indicator of the delivery personnel may include an estimated delivery time and an estimated delivery location.
  • the step of determining the estimated delivery time of the delivery person and the estimated delivery location comprises:
  • the estimated completion time of the allocated order group is calculated as the estimated delivery time and the destination address of the allocated order group as the estimated delivery location according to the allocated order group that is not currently delivered by each delivery personnel.
  • the assigned order group of the delivery person refers to an unallocated order group that has been assigned to the delivery person according to the technical solution of the exemplary embodiment of the present disclosure.
  • the estimated delivery time refers to the time when each delivery person can receive the unallocated order group
  • the estimated delivery position refers to the user position when each delivery person can receive the unallocated order group.
  • the estimated completion time of the allocated order group is determined according to the action speed of the delivery personnel, the delivery route of the allocated order group, and the user waiting time of each delivery order in the allocated order group.
  • the estimated completion time may be calculated in the manner of the above embodiment when the allocated order group is regarded as an unallocated unallocated order group.
  • the delivery indicator includes a starting address, an ending address, and a desired completion time
  • the status indicator including an estimated delivery time and an estimated delivery location, based on the delivery indicator and the status indicator
  • the time difference between the estimated delivery location of each delivery person and the starting address of each unallocated order group, the expected delivery time, and the expected delivery time of each unallocated order group, for each The familiarity of the starting point address of the assigned order group, the familiarity with the end address of each unallocated order group, the expected completion time of each unallocated order group for delivery, and the urgency of each unallocated order group or Calculate the matching score of each unallocated order group and each delivery person by multiple factors;
  • the familiarity with the starting address and the familiarity with the destination address can be advanced
  • the setting may also determine the number of times the delivery personnel arrive at the starting address according to the historical distribution record of the delivery personnel, and determine the familiarity with the starting address. The more the historical number, the higher the familiarity value; similarly, according to the history of the delivery personnel The delivery record determines the number of times the delivery personnel arrive at the destination address, and determines the familiarity. The more the history, the higher the familiarity value.
  • the urgency of the unallocated order group may be determined according to the corresponding delivery service. For example, for the second delivery service with high delivery timeliness, the urgency is higher, and for the first delivery service with low delivery timeliness, the emergency is urgent. To a lesser extent. It is also possible to determine the expected completion time according to the unallocated order group. According to the time difference between the current time and the expected completion time, the smaller the time difference, the higher the urgency.
  • the matching sub-scores of each factor can be calculated, and then the matching sub-scores of one or more factors are added or weighted summed or weighted average, that is, each unallocated order group can be calculated and obtained.
  • a matching score for a delivery person can be calculated.
  • the score corresponding to the different distance values may be preset, so that the corresponding score may be searched for as the first match according to the distance between the estimated delivery location of each delivery person and the starting address of each unallocated order group.
  • Sub-score for the sake of convenience of description, the matching sub-scores of different factors are distinguished by first, second, third, etc.;
  • the score corresponding to the different time difference values may be preset, so that the corresponding score may be searched for as the second matching sub-score according to the time difference between the expected delivery time and the expected delivery time of each unallocated order group;
  • the estimated completion time of an unallocated order group may be used to find a score corresponding to the time difference between the estimated completion time and the current time as the third matching sub-score;
  • the scores corresponding to different familiarity levels may be set in advance, so that the corresponding scores may be searched for as the fourth matching sub-score according to the familiarity with the starting address of each unallocated order group; according to the end address of each unallocated order group Familiarity, you can find the corresponding score as the fifth match sub-score;
  • the scores corresponding to different urgency levels may be set in advance, so that the corresponding sixth matching sub-score can be found according to the urgency of each unallocated order group.
  • each unallocated order group can be assigned to match Delivery staff.
  • the assigning the each unallocated order group to the matching delivery personnel according to the matching score may be: performing each unallocated order group as the Nth unallocated order group to be determined, and executing the slave Among the unmatched delivery personnel, the operation of the delivery personnel with the highest degree of matching with each unallocated order group is determined, and M allocation lists are obtained; wherein N is the total number of unallocated order groups, which is greater than or equal to 1. An integer; M is an integer greater than or equal to 1;
  • Each of the unallocated order groups is assigned to a corresponding delivery person according to an allocation list that is optimal in the list score.
  • the delivery orders of each delivery service may be first grouped in the exemplary embodiment of the present disclosure to obtain an unallocated order group for each delivery service
  • the start addresses of the respective delivery orders in each unallocated order group are mutually The distance between the distances within the first distance, the distance between the end addresses is within the second distance, and/or the time difference between the desired completion times is within a predetermined time range.
  • the unallocated unallocated order group of the at least two types of delivery services is input by the operation and maintenance personnel, or may be obtained from the respective business systems of at least two distribution services, and the business system may refer to an online transaction system and a delivery order. That is generated based on the trade order.
  • the grouping method of unallocated order groups can also be different.
  • the unallocated order group obtaining step of the first delivery service may include:
  • the user address is the sender address
  • the user address is the receiver address for the dispatch type.
  • a plurality of delivery orders that are close to the cluster center order and the user address and the user address of the cluster center order can be divided into one group.
  • a distribution order whose user address is farthest from the collection point address may be selected as a cluster center order from among the ungrouped delivery orders.
  • the packet capacity that is, the number of delivery orders included in each unallocated order group
  • the grouping capacity is used as a constraint to perform clustering processing to obtain an unallocated order group.
  • the unallocated order group obtaining step of the second delivery service may include:
  • a delivery order in which the distance between the start addresses is within the first distance, the distance between the end addresses is within the second distance, and the time difference between the desired completion times is within the preset time range is divided into the same The order group is not assigned.
  • the number of packets can be set to ensure accurate allocation of unallocated order groups and ensure the accuracy of delivery scheduling.
  • the method may further include:
  • the order completion time of each of the delivery orders is sent to the sender terminal or the recipient terminal corresponding to each delivery order.
  • the order of delivery between the groups of the assigned order groups assigned to each delivery person can be determined in the order of allocation time.
  • the expected delivery order corresponding to the matching delivery personnel can be used as the intra-group delivery order.
  • the delivery personnel can perform the delivery of the allocated order group according to the order of delivery between the groups, and for each of the allocated order groups, the delivery can be performed according to the order of delivery within the group.
  • the expected delivery order of each assigned order group can be as described in the above embodiment.
  • the unallocated order group is assigned to the delivery person, it is the assigned order group of the delivery person.
  • the data processing method may include:
  • the start address, the end address, and the expected completion time of the delivery order that are not allocated by the second delivery service may be determined
  • a delivery order in which the distance between the start addresses is within the first distance, the distance between the end addresses is within the second distance, and the time difference between the desired completion times is within the preset time range is divided into the same The order group is not assigned.
  • the status indicator may include an estimated delivery location and an estimated delivery time.
  • the estimated delivery time can be determined as follows:
  • the estimated completion time of the allocated order group is taken as the estimated delivery time according to the allocated order group whose delivery personnel are not currently delivered.
  • the estimated delivery location is the destination address of the assigned order group.
  • the delivery indicator may include a starting address, an ending address, and a desired completion time.
  • the earliest expected completion time of each delivery order in each of the unallocated order groups is taken as the expected completion time of each unallocated order group; according to each unallocated
  • the user address of each delivery order of the order group and the collection and distribution point address, and the planned delivery order of each delivery order is planned; for the pickup type, the starting address of the first delivery delivery order is used as the starting point of each unallocated order group.
  • the address, and the collection point address are the end addresses of each of the unallocated order groups.
  • the collection point address is used as the starting address of each unallocated order group, and the destination address of the last delivered delivery order is used as the end address of each unallocated order group;
  • the earliest expected completion time of each delivery order in each of the unallocated order groups is taken as the expected completion time of each of the delivery personnel for each unallocated order group;
  • the estimated delivery order of each delivery order is planned for each delivery order; the delivery of the first delivery is planned.
  • the starting address of the order is used as the starting address of each of the undistributed order groups corresponding to each of the delivery personnel, and the destination address of the last delivered delivery order as the each of the unallocated order groups The destination address of the person.
  • the expected delivery order includes a pickup order and a dispatch order, and specifically, the start address of the delivery order of the first pickup may be used as the each unallocated order group corresponding to each of the The starting address of the delivery person and the destination address of the delivery order of the last dispatch are used as the destination address of each of the undelivered order groups for each of the delivery personnel.
  • the order similarity to the assigned order group can be calculated for the delivery order that is not allocated by the second delivery service, so that A delivery order that is not assigned by the second delivery service is added to the assigned order group as a contingency order.
  • a time difference between an estimated delivery location of each of the delivery personnel and a starting address of each of the unallocated order groups, a time difference between the estimated delivery time, and an expected delivery time of each of the unallocated order groups Familiarity with the start address of each group of unallocated order groups, familiarity with the end address of each group of unallocated order groups, estimated completion time for each group of unallocated order groups for delivery, and unallocated orders for each group
  • One or more factors in the urgency of the group calculating a matching score for each unallocated order group and each delivery person.
  • the scores corresponding to different distances, different time differences, different familiarities, different urgency levels, and different expected completion times can be set, so that the scores corresponding to one or more factors are added, that is, the matching score can be calculated.
  • the estimated completion time for each distribution staff to complete each unallocated order group can be determined as follows:
  • the delivery path of each unallocated order group corresponds to the expected delivery sequence.
  • Each unassigned order group is respectively used as the Nth matched unallocated order group, and the unallocated delivery personnel are executed, and the degree of matching with each of the unallocated order groups is calculated. High distribution staff operations, obtaining M allocation lists;
  • N is the total number of unallocated order groups, which is an integer greater than or equal to 1;
  • the expected delivery order corresponding to the matching delivery personnel is used as the intra-group delivery order.
  • the sender terminal or the receiver terminal may be an electronic device capable of receiving or inquiring about the relevant delivery information of the order, such as a mobile phone or a tablet computer.
  • the first distribution service can be a floor distribution service
  • the second distribution service can be a take-out delivery service.
  • the peak distribution can be realized and can be shared.
  • the same batch of delivery personnel can save on distribution costs.
  • the system can directly assign unallocated order groups to matching delivery personnel without the need for traditional manual sorting methods, reducing the reliance on skilled workers and eliminating the need for a single delivery person to be responsible for the distribution mode for individual areas. Thereby, the distribution efficiency can be improved, and the waste of resources caused by the redundancy of the distribution personnel can be avoided.
  • FIG. 3 is a schematic structural diagram of a data processing apparatus according to an exemplary embodiment of the present disclosure, and the apparatus may include:
  • the order obtaining module 301 is configured to obtain unallocated order groups of at least two types of delivery services, respectively.
  • the first indicator determining module 302 is configured to determine a status indicator of the delivery personnel
  • a second indicator determining module 303 configured to determine a delivery indicator of the unallocated order group
  • the first order allocation module 304 is configured to allocate the unallocated order group to the matching delivery personnel based on the delivery indicator and the status indicator.
  • the distribution cost can be greatly reduced, the distribution workload can be balanced, and the distribution orders can be found according to the distribution indicators and the status indicators.
  • the delivery staff realizes automatic scheduling and eliminates the need for manual sorting, maximizing the distribution efficiency.
  • at least two kinds of distribution services include the first delivery service and the second delivery service, since the peak delivery period is different, the delivery workload of different time periods can be supplemented each other, and the delivery pressure is balanced.
  • the first order allocation module may include:
  • An order determining unit configured to determine a delivery person that matches the unallocated order group based on the delivery indicator and the status indicator;
  • an order allocation unit configured to allocate the unallocated order group to the matching delivery personnel in response to the determination result that the unallocated order group satisfies the scheduling condition.
  • the scheduling condition may be that the allocated order group of the delivery personnel matching the unallocated order group is completed.
  • the scheduling condition may be that the time difference between the expected completion time of the unallocated order group and the current time is less than a preset value, that is, the current time is close to the expected completion time.
  • the apparatus can also include:
  • a second order allocation module configured to add an unallocated order group similar to an assigned order group of any of the delivery personnel to the allocated order group according to the distance between the start address and the distance between the end addresses.
  • the first order allocation module can be specifically configured to:
  • a matching score of the unallocated order group and each delivery person may be calculated; and each unallocated order group is allocated to a matching delivery person according to the matching score.
  • the global optimal solution can be used to determine the delivery personnel that match each unallocated order group.
  • each unallocated order group is used as the Nth unallocated order group to be determined, and the unmatched order is executed.
  • identify each unallocated order group that does not match The operation of the most matching delivery personnel obtains M allocation lists; wherein N is the total number of unallocated order groups, which is an integer greater than or equal to 1; M is an integer greater than or equal to 1; M ⁇ N*(N-1 *(N-2)*-2; 1; for each allocation list, calculating a sum of matching scores corresponding to each unallocated order group, obtaining a list score for each of the allocation lists; An excellent distribution list, assigning each of the unallocated order groups to a corresponding delivery person.
  • the order acquiring module may be specifically configured to:
  • An unallocated order group of the at least two types of delivery services is obtained separately for each preset scheduling time.
  • a data processing apparatus is different from the embodiment shown in FIG. 3 in that the at least two types of distribution services may include a first delivery service. And the second distribution business.
  • the delivery type of the first delivery service includes a delivery type that extracts the delivery object from the collection point and delivers to the recipient, and a pickup type that extracts the delivery object from the sender and delivers the delivery object to the collection point;
  • the delivery type of the second delivery service is to receive the delivery object from the sender and deliver it to the recipient.
  • the device can also include:
  • the similarity calculation module 305 is configured to calculate, according to the distance between the start address and the distance between the end addresses, an allocated order group of each delivery person, an unallocated order group of the first delivery service, and the second Order similarity of the delivery order that is not assigned by the distribution business;
  • a third order allocation module 306 configured to add an unallocated order group of the first delivery service and/or a second delivery service unallocated delivery order with an order similarity greater than a similar threshold to each of the delivery The assigned order group for the person.
  • the device may further include:
  • a first order dividing module configured to select a cluster center order according to a distance between the ungrouped delivery order and the collection point address in the first delivery service
  • a second order dividing module configured to determine a starting address, an ending address, and a desired completion time of the delivery order that is not allocated by the second delivery service
  • a delivery order in which the distance between the start addresses is within the first distance, the distance between the end addresses is within the second distance, and the time difference between the desired completion times is within the preset time range is divided into the same The order group is not assigned.
  • the delivery indicator includes a start address, an end address, and a desired completion time
  • the first indicator determining module may include:
  • a first determining unit configured, for each unallocated order group of the first delivery service, an earliest expected completion time of each delivery order in each of the unallocated order groups as the unallocated order group Expected completion time; plan the expected delivery order of each delivery order according to the user address of each delivery order of each unallocated order group and the collection point address; for the pickup type, the starting address of the first delivery delivery order is taken as the Determining a starting address of each unallocated order group, and the collection point address as an end address of each unallocated order group; for a dispatch type, using the collection point address as each of the unallocated order groups The starting address of the delivery order and the destination address of the last delivered delivery order as the destination address of each of the unallocated order groups;
  • a second determining unit configured, for each unallocated order group of the second delivery service, an earliest expected completion time of each delivery order in each of the unallocated order groups as corresponding to each unallocated order group
  • the expected completion time of each delivery personnel according to the starting address, the destination address, and the estimated delivery location of each delivery person of each unallocated order group, the planned delivery of each delivery order for each delivery order is planned.
  • the starting point address of the first delivery delivery order is used as the starting address of each of the undelivered order groups corresponding to each of the delivery personnel, and the destination address of the last delivered delivery order as each of the unallocated The order group's destination address for each of the above-mentioned delivery personnel.
  • the status indicator of each of the delivery personnel includes an estimated delivery time and an estimated delivery location
  • the first order allocation module may include:
  • a first calculating unit configured to: according to the estimated delivery location of each delivery person a distance of a starting address of each unallocated order group, a time difference between the estimated delivery time and a desired delivery time of each unallocated order group, a familiarity with a starting address of each unallocated order group, One or more factors of the familiarity of the end address of each unallocated order group, the expected completion time of the delivery of each unallocated order group, and the urgency of each unallocated order group, Calculate the matching score of each unallocated order group and each delivery person;
  • a first order allocation unit configured to allocate each of the unallocated order groups to the matching delivery personnel according to the matching score.
  • the first order allocation unit may be specifically configured to: use each unallocated order group as the Nth unallocated order group to be determined, perform unmatched delivery personnel, determine and match For each operation of the undistributed order group with the highest degree of matching, obtain M allocation lists; where N is the total number of unallocated order groups, which is an integer greater than or equal to 1; M is an integer greater than or equal to 1;
  • Each unallocated order group is assigned to a corresponding delivery person according to an allocation list with an optimal list score.
  • the second indicator determining module may be specifically configured to:
  • the estimated completion time of the allocated order group is used as the estimated delivery time and the destination address of the allocated order group as the estimated delivery location according to the allocated order group whose delivery personnel are not currently delivered.
  • the device may further include:
  • a first time determining module configured to determine, according to a delivery path of each unallocated order group, a speed of movement of each of the delivery personnel, and a user waiting time of each delivery order, each delivery person is expected to complete each delivery order Order completion time;
  • a second time determining module configured to calculate, according to the order completion time, an estimated completion time of each of the unallocated order groups that each of the delivery personnel is expected to complete.
  • the device may further include:
  • the third time determination module determines, for each assigned order group, a matching match
  • the delivery personnel are expected to complete the order completion time for each of their delivery orders
  • the time prompting module is configured to send an order completion time of each of the delivery orders to a sender terminal or a receiver terminal corresponding to each delivery order.
  • the structure of the data processing apparatus can be implemented as a data processing apparatus.
  • the processing apparatus can include a processing component 501 and a storage component. 502.
  • the storage component 502 is configured to store a program that supports a data processing apparatus executing the data processing method of any of the above embodiments, the processing component 501 being configured to execute a program stored in the storage component 502.
  • the storage component 502 is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processing component 501.
  • the processing component 501 is configured to: respectively obtain an unallocated order group of at least two types of delivery services;
  • processing component 501 is further configured to perform all or part of the foregoing method steps.
  • the structure of the data processing device may further include a communication interface for the data processing device to communicate with other devices or a communication network.
  • the exemplary embodiments of the present disclosure also provide a computer storage medium for storing computer software instructions for use with the data processing apparatus, comprising a program for performing the data processing method of any of the above embodiments.
  • the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, as part of the unit display. It may or may not be a physical unit, that is, it may be located in one place, or it may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the embodiment. Those of ordinary skill in the art can understand and implement without deliberate labor.

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Abstract

一种数据处理方法，所述方法包括：分别获得至少两种配送业务的未分配订单组（101）；确定配送人员的状态指标（102）；确定所述未分配订单组的配送指标（103）；基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员（104），实现了将至少两种配送业务的配送订单进行融合调度，从而降低了配送成本，节省了配送资源，提高了配送资源的利用率。提供一种数据处理装置、设备及计算机可读存储介质。

Description

数据处理方法、装置、设备及计算机可读存储介质 技术领域
本公开实施例涉及计算机应用技术领域，尤其涉及一种数据处理方法、装置、设备及计算机可读存储介质。
背景技术
电子商务时代的到来，也带动了物流服务的飞速发展，为了满足不同配送需求，提供物流服务的配送业务也越来也多样化。
在配送业务进行配送调度时，需要配送人员参与完成，由配送人员根据配送订单完成取件和/或派件等操作。由于不同配送业务应对的配送需求可能不一样，因此配送调度方式也不一样，这就导致了目前配送业务均使用的是各自独立的配送人员进行配送调度，这无疑增加了配送成本，导致配送资源的浪费。
发明内容
为了应对各自的配送需求，目前的配送业务均使用的各自独立的配送人员进行配送调度，而发明人在研究中发现，各种配送业务为了保证服务质量，通常是按照最大配送压力配置配送人员，配送人员在某些情况下非常冗余，导致配送资源的浪费，且目前的大部分配送业务的配送调度方式通常都是由人工执行，采用人工分拣配送订单的方式进行配送调度，对配送人员的经验要求较高，存在错分问题，也会影响配送效率。
为了解决上述技术问题，本公开实施例提供了一种数据处理方法、装置、设备及计算机可读存储介质，用以降低配送成本，提高配送资源利用率，保证配送效率。
本公开实施例的第一方面提供了一种数据处理方法，包括：
分别获得至少两种配送业务的未分配订单组；
确定配送人员的状态指标；
确定所述未分配订单组的配送指标；
基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
可选地，所述基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员，包括：
基于所述配送指标以及所述状态指标，确定与所述未分配订单组相匹配的配送人员；
响应于所述分配订单组满足调度条件的判断结果，将所述未分配订单组分配至相匹配的配送人员。
可选地，所述方法还包括：
根据起点地址之间的距离以及终点地址之间的距离，将与每一配送人员的已分配订单组相似的未分配订单组加入至所述已分配订单组。
可选地，所述至少两种配送业务包括第一配送业务以及第二配送业务。
可选地，所述至少两种配送业务包括第一配送业务以及第二配送业务；
所述第一配送业务的配送类型包括从集散点提取配送对象并送达至接收方的派件类型、以及从寄送方提取配送对象并送达至所述集散点的取件类型；
所述第二配送业务的配送类型为从寄送方接收配送对象并配送至接收方。
可选地，获得所述第一配送业务的未分配订单组，包括：
根据所述第一配送业务中未分组的配送订单与集散点地址的距离，选择聚类中心订单；
根据所述未分组的配送订单与所述聚类中心订单的用户地址之间的距离进行聚类处理，以获得所述聚类中心订单对应的未分配订单组。
可选地，获得所述第二配送业务的未分配订单组，包括：
确定所述第二配送业务未分配的配送订单的起点地址、终点地址以及期望完成时间；
将起点地址彼此之间的距离在第一距离范围内、终点地址彼此之间的距离在第二距离范围内、以及期望完成时间彼此之间的时间差位于预设时间范围内的配送订单划分入同一未分配订单组。
可选地，所述配送指标包括起点地址、终点地址以及期望完成时间；
确定所述第一配送业务的每一个未分配订单组的配送指标，包括：
将所述每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组的期望完成时间；
根据所述每一未分配订单组的各个配送订单的用户地址以及集散点地址，规划各个配送订单的预计配送顺序；
针对取件类型，将第一个配送的配送订单的起点地址作为所述每一未分配订单组的起点地址，以及所述集散点地址作为所述每一未分配订单组的终点地址；
针对派件类型，将所述集散点地址作为所述每一未分配订单组的起点地址，以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组的终点地址；
确定所述第二配送业务的每一个未分配订单组的配送指标，包括：
将所述每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组对应每一配送人员的期望完成时间；
根据每一未分配订单组的各个配送订单的起点地址、终点地址以及所述每一配送人员的预计配送位置，规划各个配送订单对应每一个配送人员的预计配送顺序；
将第一个配送的配送订单的起点地址作为所述每一未分配订单组对应所述每一配送人员的起点地址、以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组对所述每一配送人员的终点地址。
可选地，所述每一配送人员的状态指标包括预计配送时间以及预计配送位置；
所述基于所述配送指标以及所述状态指标，分配所述未分配订单组 至相匹配的配送人员，包括：
根据每一配送人员的所述预计配送位置与所述每一未分配订单组的起点地址的距离、所述预计配送时间与所述每一未分配订单组的期望送达时间的时间差、对所述每一未分配订单组的起点地址的熟悉程度、对所述每一未分配订单组的终点地址的熟悉程度、配送完成所述每一未分配订单组的预计完成时间、所述每一未分配订单组的紧急程度中的一个或多个因素，计算所述每一未分配订单组与所述每一配送人员的匹配分数；
根据所述匹配分数，分配所述每一未分配订单组至相匹配的配送人员。
可选地，所述基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员包括：
将所述每一未分配订单组分别作为第N个待确定的未分配订单组，执行从未匹配的配送人员中，确定与未匹配的每一未分配订单组匹配程度最高的配送人员的操作，获得M个分配列表；其中，N为未分配订单组的总数量，为大于等于1的整数；M为大于等于1的整数；
针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；
按照列表分数最高的分配列表，分配所述每一未分配订单组至对应的配送人员。
可选地，确定所述配送人员的所述预计配送时间以及所述预计配送位置，包括：
根据所述配送人员当前未配送完成的已分配订单组，将所述已分配订单组的预计完成时间作为所述预计配送时间、所述已分配订单组的终点地址作为所述预计配送位置。
可选地，所述每一配送人员配送完成每一未分配订单组的预计完成时间按照如下方式确定：
根据所述每一未分配订单组的配送路径、所述每一配送人员的行动速度以及所述每一未分配订单组中每一配送订单的用户等待时间，确定 每一配送人员预计完成所述每一配送订单的订单完成时间；
根据所述订单完成时间，计算所述每一配送人员预计完成所述每一未分配订单组的预计完成时间。
可选地，基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员之后，还包括：
针对每一已分配订单组，确定与其相匹配的配送人员预计完成其每一配送订单的订单完成时间；
将所述每一配送订单的订单完成时间发送至所述每一配送订单对应的寄送方终端或接收方终端。
可选地，所述方法还包括：
基于起点地址之间的距离以及终点地址之间的距离，计算每一配送人员的已分配订单组分别与所述第一配送业务的未分配订单组以及所述第二配送业务未分配的配送订单的订单相似度；
将订单相似度大于相似阈值的所述第一配送业务的未分配订单组和/或所述第二配送业务未分配的配送订单，加入至所述已分配订单组。
本公开实施例的第二方面提供了一种数据处理装置，包括：
订单获取模块，用于分别获得至少两种配送业务未分配的未分配订单组；
第一指标确定模块，用于确定配送人员的状态指标；
第二指标确定模块，用于确定所述未分配订单组的配送指标；
第一订单分配模块，用于基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
可选地，所述第一订单分配模块包括：
订单确定单元，用于基于所述的配送指标以及所述状态指标，确定与所述未分配订单组相匹配的配送人员；
订单分配单元，用于响应于任一未分配订单组满足调度条件的判断结果，将所述任一未分配订单组分配至相匹配的配送人员。
可选地，所述装置还包括：
第二订单分配模块，用于根据起点地址之间的距离以及终点地址之 间的距离，将与任一配送人员的已分配订单组相似的未分配订单组加入至所述已分配订单组。
可选地，所述至少两种配送业务中包括第一配送业务以及第二配送业务。
可选地，所述至少两种配送业务中包括第一配送业务以及第二配送业务；所述第一配送业务的配送期限大于所述第二配送业务的配送期限；所述第一配送业务与所述第二配送业务的配送高峰期不同；
所述第一配送业务的配送类型包括从集散点提取配送对象并送达至接收方的派件类型、以及从寄送方提取配送对象并送达至所述集散点的取件类型；
所述第二配送业务的配送类型为从寄送方接收配送对象并配送至接收方。
可选地，所述装置还包括：
第一订单划分模块，用于根据所述第一配送业务中未分组的配送订单与集散点地址的距离，选择聚类中心订单；以及
根据所述未分组的配送订单与所述聚类中心订单的用户地址之间的距离进行聚类处理，以获得所述聚类中心订单对应的未分配订单组。
可选地，所述装置还包括：
第二订单划分模块，用于确定所述第二配送业务未分配的配送订单的起点地址、终点地址以及期望完成时间；以及
将起点地址彼此之间的距离在第一距离范围内、终点地址彼此之间的距离在第二距离范围内、以及期望完成时间彼此之间的时间差位于预设时间范围内的配送订单划分入同一未分配订单组。
可选地，所述配送指标包括起点地址、终点地址以及期望完成时间；
所述第一指标确定模块包括：
第一确定单元，用于针对所述第一配送业务的每一未分配订单组，将所述每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组的期望完成时间；根据每一未分配订单组的各个配送订单的用户地址以及集散点地址，规划各个配送订单的预计配送顺序； 针对取件类型，将第一个配送的配送订单的起点地址作为所述每一未分配订单组的起点地址，以及所述集散点地址作为所述每一未分配订单组的终点地址；针对派件类型，将所述集散点地址作为所述每一未分配订单组的起点地址，以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组的终点地址；
第二确定单元，用于针对所述第二配送业务的每一未分配订单组，将所述每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组对应每一配送人员的期望完成时间；根据每一未分配订单组的各个配送订单的起点地址、终点地址以及所述每一配送人员的预计配送位置，规划各个配送订单对应每一配送人员的预计配送顺序；将第一个配送的配送订单的起点地址作为所述每一未分配订单组对应所述每一配送人员的起点地址、以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组对所述每一配送人员的终点地址。
可选地，所述配送人员的状态指标包括预计配送时间以及预计配送位置；
所述第一订单分配模块包括：
第一计算单元，用于根据每一配送人员的所述预计配送位置与所述每一未分配订单组的起点地址的距离、所述预计配送时间与所述每一未分配订单组的期望送达时间的时间差、对每一未分配订单组的起点地址的熟悉程度、对每一未分配订单组的终点地址的熟悉程度、配送完成每一未分配订单组的预计完成时间、所述每一未分配订单组的紧急程度中的一个或多个因素，计算所述每一未分配订单组与所述每一配送人员的匹配分数；
第一订单分配单元，用于根据所述匹配分数，分配所述每一未分配订单组至相匹配的配送人员。
可选地，所述第一订单分配单元具体用于：将每一未分配订单组分别作为第N个待确定的未分配订单组，执行从未匹配的配送人员中，确定与未确定的每一未分配订单组匹配程度最高的配送人员的操作，获得M个分配列表；其中，N为未分配订单组的总数量，为大于等于1的整 数；M为大于等于1的整数；
针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；
按照列表分数最优的分配列表，分配所述每一未分配订单组至对应的配送人员。
可选地，所述第二指标确定模块具体用于：
根据所述配送人员当前未配送完成的已分配订单组，将所述已分配订单组的预计完成时间作为所述预计配送时间、所述已分配订单组的终点地址作为所述预计配送位置。
可选地，所述装置还包括：
第一时间确定模块，用于根据每一未分配订单组的配送路径、所述每一配送人员的行动速度以及所述每一未分配订单组中每一配送订单的用户等待时间，确定每一配送人员预计完成每一配送订单的订单完成时间；
第二时间确定模块，用于根据所述订单完成时间，计算所述每一配送人员预计完成所述每一未分配订单组的预计完成时间。
可选地，所述装置还包括：
第三时间确定模块，针对每一已分配订单组，确定与其相匹配的配送人员预计完成其每一配送订单的订单完成时间；
时间提示模块，用于将所述每一配送订单的订单完成时间发送至所述每一配送订单对应的寄送方终端或接收方终端。
可选地，所述装置还包括：
相似度计算模块，用于基于起点地址之间的距离以及终点地址之间的距离，计算每一配送人员的已分配订单组与所述第一配送业务的未分配订单组以及所述第二配送业务未分配的配送订单的订单相似度；
第三订单分配模块，用于将订单相似度大于相似阈值的所述第一配送业务的未分配订单组和/或所述第二配送业务未分配的配送订单，加入至所述已分配订单组。
本公开实施例的第三方面提供了一种数据处理设备，包括处理组件 以及存储组件；
所述存储组件用于存储一条或多条计算机指令，其中，所述一条或多条计算机指令被所述处理组件执行以实现：
分别获得至少两种配送业务未分配的未分配订单组；
确定配送人员的状态指标；
确定所述未分配订单组的配送指标；
基于所述配送指标以及所述状态指标，分配所述每一未分配订单组至相匹配的配送人员。
本公开实施例的第四方面提供了一种计算机可读存储介质，其上存储有计算机指令，该计算机指令被处理器执行时实现以下步骤：
分别获得至少两种配送业务的未分配订单组；
确定配送人员的状态指标；
确定所述未分配订单组的配送指标；
基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
通过本公开实施例，实现了将至少两种配送业务的配送订单的融合调度，从而使得至少两种配送业务可以共用同一批配送人员，降低了配送成本，使得配送资源得到了充分利用，避免了配送资源浪费，且实现了配送订单的自动配送调度，无需人工分拣，保证了配送效率。
本公开的这些方面或其他方面在以下实施例的描述中会更加简明易懂。
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具体实施方式
为了使本技术领域的人员更好地理解本公开方案，下面将结合本公开示例性实施例中的附图，对本公开示例性实施例中的技术方案进行清楚、完整地描述。
在本公开的说明书和权利要求书及上述附图中的描述的一些流程中，包含了按照特定顺序出现的多个操作，但是应该清楚了解，这些操作可以不按照其在本文中出现的顺序来执行或并行执行，操作的序号如101、102等，仅仅是用于区分开各个不同的操作，序号本身不代表任何的执行顺序。另外，这些流程可以包括更多或更少的操作，并且这些操作可以按顺序执行或并行执行。需要说明的是，本文中的“第一”、“第二”等描述，是用于区分不同的消息、设备、模块等，不代表先后顺序，也不限定“第一”和“第二”是不同的类型。
正如背景技术中所述，提供物流服务的配送业务越来越多样化，不同配送业务为了解决不同配送需求，通常使用各自独立的配送人员进行配送调度，以目前常见的两种配送业务为例进行说明，为了方便描述命名为第一配送业务以及第二配送业务。其中，第一配送业务的配送类型包括取件类型以及派件类型，取件类型是指从寄送方提取配送对象并送 达至集散点，派件类型是指从集散点提取配送对象并送达至接收方，因此第一配送业务的配送订单可以为取件订单或者派件订单，第一配送业务的配送操作可以为取件操作或者派件操作。在实际应用中，比如落地配即属于第一配送业务，普通的快递业务即为一种典型的落地配业务。对于取件类型，从寄送方获取的配送对象均被送至集散点等待配送，对于派件类型，配送对象均从集散点提取以配送至接收方。其中，配送对象例如可以是指各种物品，具体可以是基于网上交易获得的商品。
第二配送业务的配送类型是指从寄送方接收配送对象并配送至接收方，可以是按照期望完成时间进行配送，第二配送业务的配送操作包括取件操作以及派件操作，在实际应用中，比如基于O2O(Online To Offline，线上到线下)实现的外卖应用使用的外卖配送即属于第二配送业务的典型应用。
发明人在研究中发现，第一配送业务以及第二配送业务的配送高峰期不一样，以落地配配送业务和外卖配送业务为例，落地配配送业务的派件高峰期例如可能在每天8-11点，取件高峰期例如可能在每天7-9点，而外卖配送业务的配送高峰期例如可能在11-13点和17-19点的就餐高峰期。上述两种配送业务在各自的配送低峰期均有较大的人力浪费，这也是造成配送成本较高的一个主要原因。
为了解决配送成本较高，人力资源浪费的问题，发明人进一步发现，除了不同配送业务的配送高峰期可能不一样，在派送及时性的要求方面可能也不一样，比如第一配送业务以及第二配送业务配送期限不同，所述第一配送业务的配送订单的配送期限大于所述第二配送业务的配送订单的配送期限；
配送期限可以是指从配送订单生成时刻到配送订单配送完成时刻之间的时间长度，第一配送业务的配送订单的配送期限大于所述第二配送业务的配送订单的配送期限，也即表明第一配送业务的配送及时性低于第二配送业务的配送及时性，例如第一配送业务可以是从订单生成时刻开始之后的24小时内完成配送订单即可，而第二配送业务可能需要从订单生成时刻开始之后的半个小时内完成配送订单。因此如果将不同 配送业务的配送订单融合进行调度，使用同一批配送人员，就可以相互错峰配送，从而可以减少配送人员的数量，达到节省成本的目的。基于这一考虑，本公开示例性实施例提供了一种数据处理方法、装置、处理设备及计算机可读存储介质，以实现如何融合调度，达到节省成本，提高配送资源利用率的目的。
下面将结合本公开示例性实施例中的附图，对本公开示例性实施例中的技术方案进行清楚、完整地描述，显然，所描述的示例性实施例仅仅是本公开一部分实施例，而不是全部的实施例。基于本公开中的实施例，本领域技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
图1为本公开示例性实施例提供的一种数据处理方法的流程图，该方法可以包括以下几个步骤：
101：分别获得至少两种配送业务的未分配订单组。
举例来说，每种配送业务的未分配订单组由对未分配的配送订单进行分组获得。每种配送业务包括一个或多个未分配订单组。
根据实际需求可以针对两种或者多种不同的配送业务的配送订单进行配送调度。
其中，未分配订单组包括至少一个配送订单。
由于每一次调度时，一种配送业务的配送订单可能包括很多，而为了优化调度效果，保证配送效率，发明人研究发现，可以将每一种配送业务的配送订单进行分组，以使得每一未分配订单组中的各个配送订单的起点地址接近、终点地址接近和/或期望完成时间接近。例如，同一未分配订单组中各个配送订单的起点地址彼此之间的距离位于第一距离范围内、终点地址彼此之间的距离位于第二距离范围内、和/或期望完成时间彼此之间的时间差位于预设时间范围内。配送订单的具体分组方案在下面实施例中会详细进行介绍。
其中，对于第一配送业务，配送订单的期望完成时间可以是指配送对象送达至接收方的期望送达时间或者从寄送方接收配送对象的期望 接收时间；对于第二配送业务，配送订单的期望完成时间可以是指配送对象送达至接收方的期望送达时间。举例来说，配送订单的期望完成时间可以为某一个具体时刻，例如8:40；其可以是用户提供的，或者系统根据历史规律设置的，比如对于第一配送业务，由于其配送及时性要求不高，在配送期限内送达即可，因此期望完成时间可以设置为配送期限内的任意时刻；对于第二配送业务，由于对于配送及时性要求较高，因此期望完成时间可以根据配送订单的生成时间以及配送对象的最大配送时长确定，最大配送时长可以根据接收方与寄送方之间的最远距离、配送人员的最小行动速度等计算获得。
当然，在特殊情况下，每一个未分配订单组可以只包括一个配送订单，也即可以针对不同配送业务的配送订单无需进行分组，可以采用本公开技术方案直接进行融合调度。
102：确定配送人员的状态指标。
作为一种可能的实现方式，状态指标可以至少包括预计配送位置。该预计配送位置可以是指配送人员能够进行配送的时刻所在的人员位置。
该状态指标还可以包括预计配送时间，该预计配送时间即是配送人员能够进行配送的时刻，例如8:00。
其中，配送人员如果不存在未配送完成的配送订单，则预计配送位置即为配送人员当前所在的人员位置，预计配送时间即为当前时刻。如果存在未配送完成的配送订单，预计配送时间为最后一个配送订单配送完成的时刻，预计配送位置即为最后一个配送订单配送完成时所在的人员位置，在下面实施例中会详细进行介绍。
103：确定所述未分配订单组的配送指标。
作为一种可能的实现方式，配送指标可以至少包括起点地址。
由于一个未分配订单组中可能包括多个配送订单，每一个配送订单均会对应一个起点地址以及一个终点地址。例如，对于第一配送业务， 如果配送类型为取件类型，则起点地址即为寄送方地址，而终点地址为集散点地址，如果配送类型为派件类型，则起点地址为集散点地址，而终点地址为接收方地址，当然在某些特殊情况下，对于第一配送业务，如果配送订单出现故障，如配送对象无法妥投，则起点地址以及终点地址均为集散点地址；又如，对于第二配送业务，起点地址即为寄送方地址，而终点地址即为接收方地址。未分配订单组的起点地址可以为该未分配订单组中第一个配送的配送订单的起点地址。
为了进一步提高配送准确度，可选地，该配送指标还可以包括期望完成时间，例如可以将每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组的期望完成时间。可选地，该配送指标还可以包括终点地址。例如，未分配订单组的终点地址可以为该未分配订单组中预计最后一个配送的配送订单的终点地址。
104：基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
例如，可以根据每一未分配订单组的起点地址与每一配送人员的预计配送位置之间的距离远近，将每一未分配订单组分配至相匹配的配送人员，距离越近，表明未分配订单组与配送人员的匹配程度越高。
为了保证配送效率以及配送准时率，例如，可以在当前的配送调度周期内，为每一个配送人员仅分配一个未分配订单组。
本实施例中，通过将至少两种配送业务的配送订单进行融合调度，共用同一批配送人员，可以大大降低配送成本，均衡配送工作量，基于配送指标以及状态指标，可以为配送订单找到合适的配送人员，实现了自动调度，无需人工分拣，最大化了配送效率。至少两种配送业务包括第一配送业务以及第二配送业务时，由于配送高峰期不一样，从而可以相互补充不同时段的配送工作量，均衡配送压力。
其中，根据所述配送指标以及所述状态指标，可以计算每一未分配订单组与每一配送人员的匹配分数；从而根据所述匹配分数，可以分配所述每一未分配订单组至相匹配的配送人员。
可选地，根据所述匹配分数，可以采用全局最优解将所述每一未分 配订单组分配至相匹配的配送人员。
因此在某些实施例中，所述根据匹配分数的分配步骤可以具体包括：
将每一未分配订单组分别作为第N个待确定的未分配订单组，执行从未匹配的配送人员中，确定与未匹配的每一未分配订单组匹配程度最高的配送人员的操作，获得M个分配列表；其中，N为未分配订单组的总数量，为大于等于1的整数；M为大于等于1的整数；M≤N*(N-1)*(N-2)*-2*1；
针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；
按照列表分数最优的分配列表，分配所述未分配订单组至对应的配送人员。
为了方便理解，举例说明如下：
假设存在2个未分配订单组A、B；以及3个配送人员X、Y、Z。可以计算获得每一个未分配订单组分别与3个配送人员的匹配分数，假设A与X的匹配分数为PAX，A与Y的匹配分数为PAY，A与Z的匹配分数为PAZ；B与X的匹配分数为PBX，B与Y的匹配分数为PBY，B与Z的匹配分数为PBZ；
A作为第一个待确定的未分配订单组，根据匹配分数PAX、PAY、PAZ，从X、Y、Z中选择匹配程度最高的一个配送人员，假设匹配程度最高的为PAX对应的X；B作为第二个待确定的未分配订单组，由于A已经选择X，则B从未匹配的Y、Z中选择匹配程度最高的一个配送人员，假设匹配程度最高的为PBZ对应的Z，此时获得的分配列表为：A分配至X；B分配至Z；计算PAX和PBZ的匹配分数之和，假设为R1，可以作为分配列表的列表分数；
以此类推，A作为第二个待确定的未分配订单组，B作为第一个待确定的未分配订单组，假设获得的分配列表为A分配至Y；B分配至X；计算PAY和PBZ的匹配分数之和，假设为R2，可以作为该分配列表的类别分数；
由上述描述可知，A作为第一个待确定的未分配订单组时，A优先 从X、Y、Z中选择了匹配程度最高的配送人员X，B作为第二待确定的未分配订单组，只能从Y、Z中选择匹配程度最高的配送人员为Z，而B作为第一个待确定的未分配订单组时，可以优先从X、Y、Z中选择了匹配程度最高的配送人员为X，A只能从Y、Z选择匹配程度最高的配送人员为Y，因此A与B分别作为第N个待确定的未分配订单组时，得到的分配列表可能并不相同。
比较R1和R2，即可以确定出列表分数最优的一个分配列表，假设为R2最优，则按照R2对应的分配列表进行分配，也即A分配至Y；B分配至X。
其中，如果匹配分数越大，表明匹配程度越高，则列表分数越大，表明列表分数越优；反之，如果匹配分数越小，表明匹配程度越高，则列表分数越小，表明列表分数越优。
可选地，如果不存在与任一未分配订单组匹配的配送人员，例如未分配订单组的个数大于配送人员个数时，每一配送人员均只分配一个未分配订单组时，就会存在剩余未分配订单组待分配，则可以返回步骤101继续执行。
在某些实施例中，可选地，分别获得至少两种配送业务的未分配订单组可以包括：
每间隔预设调度时间，分别获得所述至少两种配送业务的未分配订单组。也即周期性进行配送调度，以保证调度准确率，保证配送效率。
当然在某些特殊情况下，也可以实时进行配送调度。
其中，将配送订单分组得到未分配订单组之后，可以为未分配订单组设置未分配标记标号，具有该未分配标记符号的订单组即为未分配订单组，从而可以是根据未分配标记符号，分别获得至少两种配送业务的未分配订单组。在某些实施例中，可选地，基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员可以包括：
基于所述配送指标以及所述状态指标，确定与所述未分配订单组相匹配的配送人员；
响应于所述未分配订单组满足调度条件的判断结果，将所述未分配 订单组分配至相匹配的配送人员。
也即确定出与任一未配送订单相匹配的配送人员之后，并不立即分配至配送人员，而是等待该任一未分配订单组满足调度条件时，再将其分配至相匹配的配送人员。
作为一种可能的实现方式，该调度条件可以是所述未分配订单组相匹配的配送人员的已分配订单组配送完成。也即任一未分配订单组相匹配的配送人员的已分配订单组配送完成之后，再将该任一未分配订单组分配至相匹配的配送人员。
作为又一种可能的实现方式，该调度条件可以是所述未分配订单组的期望完成时间与当前时间的时间差小于预设值，也即当前时间接近期望完成时间。也即任一未分配订单组的期望完成时间与当前时间的时间差小于预设值时，再将该任一未分配订单组分配至相匹配的配送人员。
在当前调度周期结束时，对于不满足调度条件的未分配订单组，可以返回所述分别获得至少两种配送业务的未分配订单组的步骤继续执行，以重新进行配送调度。
在某些实施例中，可选地，分别获得至少两种配送业务的未分配订单组之后，还可以包括：
根据起点地址之间的距离以及终点地址之间的距离，将与任一配送人员的已分配订单组相似的未分配订单组加入至所述已分配订单组。从而可以实现顺路配送，保证配送时效和配送效率。
已分配订单组也即是指已分配至配送人员的未分配订单组。
作为一种可选方式，例如可以是如果每一未分配订单组与任一配送人员的已分配订单组的起点地址之间的距离小于第一距离阈值，且终点地址之间的距离小于第二距离阈值时，则将所述任一未分配订单组加入所述已分配订单组，从而配送人员即可以进行配送。
作为又一种可选方式，可以是根据起点地址之间的距离以及终点地址之间的距离，计算任一配送人员的已分配订单组与每一未分配订单组的订单相似度；
将订单相似度大于相似阈值的未分配订单组加入所述已分配订单 组中。
其中起点地址之间的距离越小且终点地址之间的距离越小，即表明订单相似度越大。举例来说，可以根据不同距离范围预先设置不同的分数，从而已分配订单组与任一未分配订单组的起点地址之间的距离以及终点地址之间的距离确定之后，分别查找起点地址之间距离所在距离范围对应分数，作为第一相似度分数，以及终点地址之间的距离所在距离范围对应分数，作为第二相似度分数，将第一相似度分数以及第二相似度分数相加或者加权平均或者加权求和等，即可以计算获得订单相似度。
此外，未分配订单组可以具有期望完成时间，根据未分配订单组与已分配订单组的期望完成时间的时间差，可以计算一个第三相似度分数，例如可以预设不同时间数值范围对应的分数，查找时间差所在时间数值范围对应的分数作为第三相似度分数。将第一相似度分数、第二相似度分数以及第三相似度分数相加或者加权平均或者加权求和等，计算获得订单相似度。
从而可以将订单相似度大于相似阈值的未分配订单组，加入至所述每一配送人员的所述已分配订单组。
由上文描述可知，未分配订单组的配送指标可以包括起点地址、终点地址和/或期望完成时间。起点地址或终点地址可以结合未分配订单组中每个配送订单的预计配送顺序确定。而不同配送业务的预计配送顺序确定方式也不同。
在某些实施例中，所述至少两种配送业务可以包括第一配送业务以及第二配送业务；
所述第一配送业务配送指标的确定步骤可以包括：
将每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组的期望完成时间；根据每一未分配订单组的各个配送订单的用户地址以及集散点地址，规划各个配送订单的预计配送顺序；
针对取件类型，将第一个配送的配送订单的起点地址作为所述每一未分配订单组的起点地址，以及所述集散点地址作为所述每一未分配订单组的终点地址；
针对派件类型，将所述集散点地址作为所述每一未分配订单组的起点地址，以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组的终点地址；
其中对于第一配送业务，规划各个配送订单的预计配送顺序可以根据最小路径原则进行规则，以使得配送路径最短。最小路径原则简单来说，即是以总路径最小为原则，规划得到相应的配送路径，从而也即可以确定出配送顺序。
所述第二配送业务配送指标的确定步骤可以包括：
将每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组对应每一配送人员的期望完成时间；
根据每一未分配订单组的各个配送订单的起点地址、终点地址以及所述每一配送人员的预计配送位置，规划各个配送订单对应每一配送人员的预计配送顺序；
将第一个配送的配送订单的起点地址作为所述每一未分配订单组对应所述每一配送人员的起点地址、以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组对应所述每一配送人员的终点地址。
因此，对于第二配送业务，同一个未分配订单组对应不同配送人员的配送指标可能不同。
此外，由于第二配送业务包括从寄送方接收配送对象的取件操作，以及将配送对象配送至接收方的派件操作，因此该预计配送顺序包括取件顺序以及派件顺序；
其中，取件顺序根据各个配送订单的起点地址以及每一配送人员的预计配送位置规划获得，派件顺序根据各个配送订单的终点地址以及最后一个取件的配送订单的起点地址规划获得。
因此具体是将第一取件的配送订单的起点地址作为所述每一未分配订单组对应所述每一个配送人员的起点地址，以及最后一个派件的配送订单的终点地址作为所述每一未分配订单组对应所述每一个配送人员的终点地址。
对于第二配送业务，特别是外卖配送业务，对于完成时间要求较高， 通常期望即时送达，因此规划每一未分配订单组中各个配送订单的取件顺序可以根据取件等待时间、按照最小路径原则进行规划，以使得取件等待时间最短的情况下取件路径最短，派件顺序可以根据期望完成时间，按照最小路径原则进行规划，以使得配送完成所述未分配订单组的预计完成时间小于或等于所述期望完成时间的情况下派件路径最短。
其中，每一配送人员配送完成每一未分配订单组的预计完成时间可以按照如下方式确定：
根据每一未分配订单组的配送路径、所述每一配送人员的行动速度以及每一配送订单的用户等待时间，确定每一配送人员预计完成每一配送订单的订单完成时间；该订单完成时间可以为某一个具体时刻，例如15:30。
根据所述订单完成时间，计算所述每一配送人员预计完成所述每一未分配订单组的预计完成时间。
其中，如果该预计完成时间大于所述期望完成时间，则可以重新确定每一未分配订单组的配送路径，以保证该预计完成时间小于或等于所述期望完成时间且配送路径较短。
对于第二配送业务，该配送路径由取件路径以及派件路径构成，用户等待时间也即可以包括在寄送方的取件等待时间以及在接收方的派件等待时间。
对于第一配送业务的取件类型，用户等待时间可以包括在寄送方的取件等待时间；
对于第一配送业务的派件类型，用户等待时间可以包括在集散点的取件等待时间以及在接收方的派件等待时间。
其中，对于第一配送业务可以是在将第一配送业务的未分配订单组分配至相匹配的配送人员之后，计算未分配订单组的预计完成时间以及未分配订单组中每一配送订单的订单完成时间；对于第二配送业务可以是在确定第二配送业务的未分配订单组的配送指标时，即可以计算未分配订单组对应每一配送人员的预计完成时间以及每一配送订单对应每一配送人员的订单完成时间。当然第一配送业务也可以预先为未分配订 单组计算订单完成时间，从而将未分配订单组分配至配送人员之后，可以直接利用该订单完成时间。
其中，配送人员的状态指标可以包括预计配送时间以及预计配送位置。
在某些实施例中，所述配送人员的所述预计配送时间以及所述预计配送位置的确定步骤包括：
根据每一配送人员当前未配送完成的已分配订单组，计算所述已分配订单组的预计完成时间作为所述预计配送时间、所述已分配订单组的终点地址作为预计配送位置。
其中，配送人员的已分配订单组是指按照本公开示例性实施例的技术方案已分配至配送人员的未分配订单组。
预计配送时间即是指所述每一配送人员可以接收未分配订单组的时间，预计配送位置是指每一配送人员可以接收未分配订单组时的用户位置。
其中，所述已分配订单组的预计完成时间即是根据所述配送人员的行动速度、所述已分配订单组的配送路径以及所述已分配订单组中各个配送订单的用户等待时间确定的。该预计完成时间可以是在该已分配订单组作为未分配的未分配订单组时，按照上述实施例中的方式计算获得。
在某些实施例中，所述配送指标包括起点地址、终点地址以及期望完成时间，所述状态指标包括预计配送时间以及预计配送位置的情况下，基于所述配送指标以及所述状态指标，分配所述每一未分配订单组至相匹配的配送人员的步骤可以包括：
根据每一配送人员的预计配送位置与所述每一未分配订单组的起点地址的距离、所述预计配送时间与所述每一未分配订单组的期望送达时间的时间差、对每一未分配订单组的起点地址的熟悉程度、对每一未分配订单组的终点地址的熟悉程度、配送完成每一未分配订单组的预计完成时间、每一未分配订单组的紧急程度中的一个或多个因素，计算每一未分配订单组与每一配送人员的匹配分数；
其中，对起点地址的熟悉程度以及对终点地址的熟悉程度可以预先 设置，也可以根据配送人员的历史配送记录确定配送人员到达起点地址的历史次数，确定对起点地址的熟悉程度，其中，历史次数越多，熟悉程度值越高；同理可以根据配送人员的历史配送记录确定配送人员到达终点地址的历史次数，确定熟悉程度，其中，历史次数越多，熟悉程度值越高。
其中，未分配订单组的紧急程度可以根据对应的配送业务确定，例如对于配送及时性要求较高的第二配送业务，紧急程度较高，而对于配送及时性不高的第一配送业务，紧急程度较低。还可以根据未分配订单组的期望完成时间确定，根据当前时刻与期望完成时间的时间差，时间差越小，紧急程度越高。
其中，根据每一个因素可以计算获得每一个因素的匹配子分数，再将一个或多个因素的匹配子分数相加或者加权求和或者加权平均，即可以计算获得每一未分配订单组与每一配送人员的匹配分数。
举例来说，可以预先设置不同距离数值对应的分数，从而根据所述每一配送人员的预计配送位置与所述每一未分配订单组的起点地址的距离，可以查找对应的分数作为第一匹配子分数；为了方便描述清楚，此处以第一、第二、第三等区分不同因素的匹配子分数；
可以预先设置不同时间差数值对应的分数，从而根据所述预计配送时间与所述每一未分配订单组的期望送达时间的时间差、可以查找对应的分数作为第二匹配子分数；根据配送完成每一未分配订单组的预计完成时间，可以查找该预计完成时间与当前时间的时间差对应的分数作为第三匹配子分数；
可以预先设置不同熟悉程度对应的分数，从而根据对每一未分配订单组的起点地址的熟悉程度，可以查找对应的分数作为第四匹配子分数；根据对每一未分配订单组的终点地址的熟悉程度，可以查找对应的分数作为第五匹配子分数；
可以预先设置不同紧急程度对应的分数，从而根据每一未分配订单组的紧急程度，可以查找对应的第六匹配子分数。
根据所述匹配分数，即可以分配所述每一未分配订单组至相匹配的 配送人员。
其中，所述根据所述匹配分数，分配所述每一未分配订单组至相匹配的配送人员可以是：将每一未分配订单组分别作为第N个待确定的未分配订单组，执行从未匹配的配送人员中，确定与未匹配的每一未分配订单组匹配程度最高的配送人员的操作，获得M个分配列表；其中，N为未分配订单组的总数量，为大于等于1的整数；M为大于等于1的整数；
针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；
按照列表分数最优的一个分配列表，分配所述每一未分配订单组至对应的配送人员。
其中，每一配送人员配送完成每一未分配订单组的预计完成时间的确定可以参见上述实施例中所述。
由于本公开示例性实施例中可以首先对每一种配送业务的配送订单进行分组，以获得每一配送业务的未分配订单组，使得每一未分配订单组中各个配送订单的起点地址彼此之间的距离在第一距离范围内、终点地址彼此之间的距离在第二距离范围内、和/或期望完成时间彼此之间的时间差位于预设时间范围内。
其中，至少两种配送业务的未分配的未分配订单组以是由运维人员输入，也可以是从至少两种配送业务各自的业务系统中获取，业务系统可以是指网上交易系统，配送订单即是根据交易订单而生成的。
而对于不同配送类型的配送业务，未分配订单组的分组方式也可以不同。
在某些实施例中，所述至少两种配送业务包括第一配送业务以及第二配送业务时，所述第一配送业务的未分配订单组获得步骤可以包括：
根据所述第一配送业务中未分组的配送订单的用户地址与集散点地址的距离，选择聚类中心订单；
根据所述未分组的配送订单与所述聚类中心订单的用户地址之间的距离进行聚类处理，以获得所述聚类中心订单对应的未分配订单组。
其中，针对取件类型，用户地址即为寄送方地址，针对派件类型，用户地址即为接收方地址。
通过聚类处理，可以将聚类中心订单以及用户地址与所述聚类中心订单的用户地址接近的多个配送订单划分为一组。
可选地，可以是从未分组的配送订单中，选择用户地址距离所述集散点地址最远的一个配送订单作为聚类中心订单。
为了保证分组准确度，可以设置分组容量，也即每一未分配订单组包含的配送订单个数，以所述分组容量为约束进行聚类处理，获得一个未分配订单组。
在某些实施例中，所述第二配送业务的未分配订单组获得步骤可以包括：
确定所述第二配送业务未分配的配送订单的起点地址、终点地址以及期望完成时间；
将起点地址彼此之间的距离在第一距离范围内、终点地址彼此之间的距离在第二距离范围内、以及期望完成时间彼此之间的时间差位于预设时间范围内的配送订单划分为同一未分配订单组。
也即将起点地址接近、终点地址接近且期望完成时间接近的多个配送订单划分为同一未分配订单组。
其中，为了保证分组准确度，可以设置分组数量，以保证未分配订单组划分准确，保证配送调度的准确度。
在某些实施例中，将未分配订单组分配至相匹配的配送人员之后，还可以包括：
针对每一已分配订单组，确定与其相匹配的配送人员预计完成其每一配送订单的订单完成时间；
将所述每一配送订单的订单完成时间发送至所述每一配送订单对应的寄送方终端或接收方终端。
此外，还可以按照分配时间顺序，确定为每一配送人员分配的已分配订单组的组间配送顺序。
而对于每一已分配订单组，可以将与其相匹配的配送人员对应的预计配送顺序作为组内配送顺序。
配送人员即可以按照组间配送顺序，进行已分配订单组的配送，而对于每一个已分配订单组，可以按照组内配送顺序进行配送。
各个已分配订单组的预计配送顺序可以参见上述实施例中所述。
其中，未分配订单组分配至配送人员之后，即为该配送人员的已分配订单组。
下面以至少两种配送业务为第一配送业务以及第二配送业务为例，对本公开示例性实施例的技术方案进行详细描述，参见图2中所示，所述数据处理方法可以包括：
201：将第一配送业务未分配的配送订单进行分组，获得所述第一配送业务的未分配订单组。
可选地，可以是：
根据所述第一配送业务中未分组的配送订单与集散点地址的距离，选择聚类中心订单；
根据所述未分组的配送订单与所述聚类中心订单的用户地址之间的距离进行聚类处理，以获得所述聚类中心订单对应的未分配订单组。
202：将第二配送业务未分配的配送订单进行分组，获得所述第二配送业务的未分配订单组。
可选地，可以是确定所述第二配送业务未分配的配送订单的起点地址、终点地址以及期望完成时间；
将起点地址彼此之间的距离在第一距离范围内、终点地址彼此之间的距离在第二距离范围内、以及期望完成时间彼此之间的时间差位于预设时间范围内的配送订单划分为同一未分配订单组。
203：确定每一配送人员的状态指标。
其中，状态指标可以包括预计配送位置以及预计配送时间。
该预计配送时间可以按照如下方式确定：
根据所述配送人员当前未配送完成的已分配订单组，将所述已分配订单组的预计完成时间作为所述预计配送时间。
该预计配送位置为所述述已分配订单组的终点地址。
204：确定每一未分配订单组的配送指标。
其中，该配送指标可以包括起点地址、终点地址以及期望完成时间。
可选地，可以是：
对于第一配送业务的每一个未分配订单组，将所述每一个未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组的期望完成时间；根据每一个未分配订单组的各个配送订单的用户地址以及集散点地址，规划各个配送订单的预计配送顺序；针对取件类型，将第一个配送的配送订单的起点地址作为所述每一未分配订单组的起点地址，以及所述集散点地址作为所述每一未分配订单组的终点地址。针对派件类型，将所述集散点地址作为所述每一未分配订单组的起点地址，以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组的终点地址；
对于第二配送业务的每一个未分配订单组，将所述每一个未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组对应每一个配送人员的期望完成时间；根据每一个未分配订单组的各个配送订单的起点地址、终点地址以及所述每一配送人员的预计配送位置，规划各个配送订单对应每一个配送人员的预计配送顺序；将第一个配送的配送订单的起点地址作为所述每一未分配订单组对应所述每一个配送人员的起点地址、以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组对一个所述每一配送人员的终点地址。
其中，对于第二配业务，预计配送顺序包括取件顺序以及派件顺序，具体的可以是将第一个取件的配送订单的起点地址作为所述每一未分配订单组对应所述每一配送人员的起点地址、以及最后一个派件的配送订单的终点地址作为所述每一未分配订单组对所述每一配送人员的终点地址。
205：基于起点地址之间的距离以及终点地址之间的距离，计算每一配送人员的已分配订单组与所述第一配送业务的未分配订单组以及所述第二配送业务未分配的配送订单的订单相似度。
206：将订单相似度大于相似阈值的所述第一配送业务的未分配订单组和/或所述第二配送业务未分配的配送订单，加入至所述每一配送人员的所述已分配订单组。
举例来说，由于第二配送业务往往对配送时效要就比较严格，通常要求准时送达，因此可以针对第二配送业务未分配的配送订单，来计算与已分配订单组订单相似度，从而可以将第二配送业务未分配的配送订单作为顺路单加入已分配订单组中。
207：根据所述状态指标以及所述配送指标，计算每一未分配订单组与每一配送人员的匹配分数。
可选地，可以是：
根据所述每一配送人员的预计配送位置与所述每一组未分配订单组的起点地址的距离、所述预计配送时间与所述每一组未分配订单组的期望送达时间的时间差、对每一组未分配订单组的起点地址的熟悉程度、对每一组未分配订单组的终点地址的熟悉程度、配送完成每一组未分配订单组的预计完成时间、每一组未分配订单组的紧急程度中的一个或多个因素，计算每一未分配订单组与每一配送人员的匹配分数。
可以设置不同距离、不同时间差、不同熟悉程度、不同紧急程度、不同预计完成时间对应的分数，从而将一个或多个因素对应的分数相加，即可以计算获得匹配分数。
其中，每一配送人员配送完成每一未分配订单组的预计完成时间可以按照如下方式确定：
根据每一未分配订单组的配送路径、所述每一配送人员的行动速度以及每一配送订单的用户等待时间，确定每一配送人员预计完成每一配送订单的订单完成时间；
根据所述订单完成时间，计算所述每一配送人员预计完成所述每一未分配订单组的预计完成时间。
其中，每一未分配订单组的配送路径对应预计配送顺序。
208：将每一未分配订单组分别作为第N个匹配的未分配订单组，执行从未分配的配送人员中，计算与所述每一未分配订单组匹配程度最 高的配送人员的操作，获得M个分配列表；
其中，N为未分配订单组的总数量，为大于等于1的整数；
209：针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；
210：按照列表分数最优的分配列表，分配所述每一未分配订单组至对应的配送人员。
211：按照分配时间顺序，确定为每一配送人员分配的已分配订单组的组间配送顺序；
212：根据每一已分配订单组，将与其相匹配的配送人员对应的预计配送顺序作为组内配送顺序。
213：针对每一已分配订单组，确定与其相匹配的配送人员预计完成其每一配送订单的订单完成时间。
214：将所述每一配送订单的订单完成时间发送至所述每一配送订单对应的寄送方终端或接收方终端。
其中，该寄送方终端或者接收方终端可以为手机、平板电脑等能够接收或查询订单的相关配送信息的电子设备。
在实际应用中，第一配送业务可以为落地配业务，第二配送业务可以为外卖配送业务，通过将落地配业务以及外卖配送业务的配送订单进行融合调度，可以实现错峰配送，且可以共用同一批配送人员，可以节省配送成本。通过融合调度，系统可以直接将未分配订单组分配至相匹配的配送人员，而无需采用传统的人工分拣方式，降低了对熟练工的依赖，也无需单个配送人员负责单个区域的配送模式，从而可以提高配送效率，避免配送人员冗余导致的资源浪费问题。
图3为本公开示例性实施例提供的一种数据处理装置的结构示意图，该装置可以包括：
订单获取模块301，用于分别获得至少两种配送业务的未分配订单组。
第一指标确定模块302，用于确定配送人员的状态指标；
第二指标确定模块303，用于确定所述未分配订单组的配送指标；
第一订单分配模块304，用于基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
本实施例中，通过将至少两种配送业务的配送订单进行融合调度，共用同一批配送人员，可以大大降低配送成本，均衡配送工作量，基于配送指标以及状态指标，可以为配送订单找到合适的配送人员，实现了自动调度，无需人工分拣，最大化了配送效率。至少两种配送业务包括第一配送业务以及第二配送业务时，由于配送高峰期不一样，从而可以相互补充不同时段的配送工作量，均衡配送压力。可选地，所述第一订单分配模块可以包括：
订单确定单元，用于基于所述的配送指标以及所述状态指标，确定与所述未分配订单组相匹配的配送人员；
订单分配单元，用于响应于所述未分配订单组满足调度条件的判断结果，将所述未分配订单组分配至相匹配的配送人员。
作为一种可选的方式，该调度条件可以是所述未分配订单组相匹配的配送人员的已分配订单组配送完成。
作为又一种可选的方式，该调度条件可以是所述未分配订单组的期望完成时间与当前时间的时间差小于预设值，也即当前时间接近期望完成时间。
在某些实施例中，该装置还可以包括：
第二订单分配模块，用于根据起点地址之间的距离以及终点地址之间的距离，将与任一配送人员的已分配订单组相似的未分配订单组加入至所述已分配订单组。
在某些实施例中，所述第一订单分配模块可以具体用于：
根据所述配送指标以及所述状态指标，可以计算所述未分配订单组与每一配送人员的匹配分数；根据所述匹配分数，分配所述每一未分配订单组至相匹配的配送人员。
其中，可以采用全局最优解确定每一未分配订单组相匹配的配送人员，具体的是：将每一未分配订单组分别作为第N个待确定的未分配订单组，执行从未匹配的配送人员中，确定与未匹配的每一未分配订单组 匹配程度最高的配送人员的操作，获得M个分配列表；其中，N为未分配订单组的总数量，为大于等于1的整数；M为大于等于1的整数；M≤N*(N-1)*(N-2)*-2；1；针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；按照列表分数最优的分配列表，分配所述每一未分配订单组至对应的配送人员。
可选地，所述订单获取模块可以具体用于：
每间隔预设调度时间，分别获得所述至少两种配送业务的未分配订单组。
其中，如图4所示，为本公开示例性实施例提供的一种数据处理装置的，与图3所述实施例不同之处在于，所述至少两种配送业务中可以包括第一配送业务以及第二配送业务。
所述第一配送业务的配送类型包括从集散点提取配送对象并送达至接收方的派件类型、以及从寄送方提取配送对象并送达至所述集散点的取件类型；
所述第二配送业务的配送类型为从寄送方接收配送对象并配送至接收方。
该装置还可以包括：
相似度计算模块305，用于基于起点地址之间的距离以及终点地址之间的距离，计算每一配送人员的已分配订单组与所述第一配送业务的未分配订单组以及所述第二配送业务未分配的配送订单的订单相似度；
第三订单分配模块306，用于将订单相似度大于相似阈值的所述第一配送业务的未分配订单组和/或所述第二配送业务未分配的配送订单，加入至所述每一配送人员的所述已分配订单组。
可选地，该装置还可以包括：
第一订单划分模块，用于根据所述第一配送业务中未分组的配送订单与集散点地址的距离，选择聚类中心订单；以及
根据所述未分组的配送订单与所述聚类中心订单的用户地址之间的距离进行聚类处理，以获得所述聚类中心订单对应的未分配订单组；
第二订单划分模块，用于确定所述第二配送业务未分配的配送订单的起点地址、终点地址以及期望完成时间；以及
将起点地址彼此之间的距离在第一距离范围内、终点地址彼此之间的距离在第二距离范围内、以及期望完成时间彼此之间的时间差位于预设时间范围内的配送订单划分为同一未分配订单组。
可选地，所述配送指标包括起点地址、终点地址以及期望完成时间；
则所述第一指标确定模块可以包括：
第一确定单元，用于针对所述第一配送业务的每一个未分配订单组，将所述每一个未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组的期望完成时间；根据每一个未分配订单组的各个配送订单的用户地址以及集散点地址，规划各个配送订单的预计配送顺序；针对取件类型，将第一个配送的配送订单的起点地址作为所述每一未分配订单组的起点地址，以及所述集散点地址作为所述每一未分配订单组的终点地址；针对派件类型，将所述集散点地址作为所述每一未分配订单组的起点地址，以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组的终点地址；
第二确定单元，用于针对所述第二配送业务的每一个未分配订单组，将所述每一个未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组对应每一个配送人员的期望完成时间；根据每一个未分配订单组的各个配送订单的起点地址、终点地址以及所述每一配送人员的预计配送位置，规划各个配送订单对应每一个配送人员的预计配送顺序；将第一个配送的配送订单的起点地址作为所述每一未分配订单组对应所述每一配送人员的起点地址、以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组对一个所述每一配送人员的终点地址。
可选地，所述每一配送人员的状态指标包括预计配送时间以及预计配送位置；
所述第一订单分配模块可以包括：
第一计算单元，用于根据每一配送人员的所述预计配送位置与所述 每一未分配订单组的起点地址的距离、所述预计配送时间与所述每一未分配订单组的期望送达时间的时间差、对所述每一未分配订单组的起点地址的熟悉程度、对所述每一未分配订单组的终点地址的熟悉程度、配送完成所述每一未分配订单组的预计完成时间、所述每一未分配订单组的紧急程度中的一个或多个因素，计算每一未分配订单组与每一配送人员的匹配分数；
第一订单分配单元，用于根据所述匹配分数，分配所述每一未分配订单组至相匹配的配送人员。
可选地，所述第一订单分配单元可以具体用于：将每一未分配订单组分别作为第N个待确定的未分配订单组，执行从未匹配的配送人员中，确定与未匹配的每一未分配订单组匹配程度最高的配送人员的操作，获得M个分配列表；其中，N为未分配订单组的总数量，为大于等于1的整数；M为大于等于1的整数；
针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；
按照列表分数最优的分配列表，分配所述每一未分配订单组至对应的配送人员。
可选地，所述第二指标确定模块可以具体用于：
根据所述配送人员当前未配送完成的已分配订单组，将所述已分配订单组的预计完成时间作为所述预计配送时间、所述已分配订单组的终点地址作为所述预计配送位置。
可选地，该装置还可以包括：
第一时间确定模块，用于根据每一未分配订单组的配送路径、所述每一配送人员的行动速度以及每一配送订单的用户等待时间，确定每一配送人员预计完成每一配送订单的订单完成时间；
第二时间确定模块，用于根据所述订单完成时间，计算所述每一配送人员预计完成所述每一未分配订单组的预计完成时间。
可选地，该装置还可以包括：
第三时间确定模块，针对每一已分配订单组，确定与其相匹配的配 送人员预计完成其每一配送订单的订单完成时间；
时间提示模块，用于将所述每一配送订单的订单完成时间发送至所述每一配送订单对应的寄送方终端或接收方终端。
以上描述了数据处理装置的内部功能和结构，在一个可能的设计中，该数据处理装置的结构可实现为数据处理设备，如图5中所示，该处理设备可以包括处理组件501以及存储组件502。
所述存储组件502用于存储支持数据处理装置执行上述任一实施例中数据处理方法的程序，所述处理组件501被配置为用于执行所述存储组件502中存储的程序。
所述存储组件502用于存储一条或多条计算机指令，其中，所述一条或多条计算机指令被所述处理组件501执行。
所述处理组件501用于：分别获得至少两种配送业务的未分配订单组；
确定配送人员的状态指标；
确定所述未分配订单组的配送指标；
基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
可选地，所述处理组件501还用于执行前述各方法步骤中的全部或部分步骤。
其中，所述数据处理设备的结构中还可以包括通信接口，用于数据处理设备与其他设备或通信网络通信。
本公开示例性实施例还提供了一种计算机存储介质，用于储存所述数据处理装置所用的计算机软件指令，其包含用于执行上述任一实施例中数据处理方法所涉及的程序。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件 可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到各实施方式可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件。基于这样的理解，上述技术方案本质上或者说对相关技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行各个实施例或者实施例的某些部分所述的方法。
最后应说明的是：以上实施例仅用以说明本公开的技术方案，而非对其限制；尽管参照前述实施例对本公开进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本公开各实施例技术方案的精神和范围。

Claims (30)

  1. 一种数据处理方法，其中包括：
    分别获得至少两种配送业务的未分配订单组；
    确定配送人员的状态指标；
    确定所述未分配订单组的配送指标；
    基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
  2. 根据权利要求1所述的方法，其中，所述基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员，包括：
    基于所述配送指标以及所述状态指标，确定与所述未分配订单组相匹配的配送人员；
    响应于所述分配订单组满足调度条件的判断结果，将所述未分配订单组分配至相匹配的配送人员。
  3. 根据权利要求1所述的方法，还包括：
    根据起点地址之间的距离以及终点地址之间的距离，将与每一配送人员的已分配订单组相似的未分配订单组加入至所述已分配订单组。
  4. 根据权利要求1所述的方法，其中，所述至少两种配送业务包括第一配送业务以及第二配送业务。
  5. 根据权利要求1所述的方法，其中，所述至少两种配送业务包括第一配送业务以及第二配送业务；
    所述第一配送业务的配送类型包括从集散点提取配送对象并送达至接收方的派件类型、以及从寄送方提取配送对象并送达至所述集散点的取件类型；
    所述第二配送业务的配送类型为从寄送方接收配送对象并配送至接收方。
  6. 根据权利要求5所述的方法，其中，获得所述第一配送业务的未分配订单组，包括：
    根据所述第一配送业务中未分组的配送订单与集散点地址的距离， 选择聚类中心订单；
    根据所述未分组的配送订单与所述聚类中心订单的用户地址之间的距离进行聚类处理，以获得所述聚类中心订单对应的未分配订单组。
  7. 根据权利要求5所述的方法，其中，获得所述第二配送业务的未分配订单组，包括：
    确定所述第二配送业务未分配的配送订单的起点地址、终点地址以及期望完成时间；
    将起点地址彼此之间的距离在第一距离范围内、终点地址彼此之间的距离在第二距离范围内、以及期望完成时间彼此之间的时间差位于预设时间范围内的配送订单划分入同一未分配订单组。
  8. 根据权利要求5所述的方法，其中，所述配送指标包括起点地址、终点地址以及期望完成时间；
    确定所述第一配送业务的每一个未分配订单组的配送指标，包括：
    将所述每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组的期望完成时间；
    根据所述每一未分配订单组的各个配送订单的用户地址以及集散点地址，规划各个配送订单的预计配送顺序；
    针对取件类型，将第一个配送的配送订单的起点地址作为所述每一未分配订单组的起点地址，以及所述集散点地址作为所述每一未分配订单组的终点地址；
    针对派件类型，将所述集散点地址作为所述每一未分配订单组的起点地址，以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组的终点地址；
    确定所述第二配送业务的每一个未分配订单组的配送指标，包括：
    将所述每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组对应每一配送人员的期望完成时间；
    根据每一未分配订单组的各个配送订单的起点地址、终点地址以及所述每一配送人员的预计配送位置，规划各个配送订单对应每一个配送人员的预计配送顺序；
    将第一个配送的配送订单的起点地址作为所述每一未分配订单组对应所述每一配送人员的起点地址、以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组对所述每一配送人员的终点地址。
  9. 根据权利要求8所述的方法，其中，所述每一配送人员的状态指标包括预计配送时间以及预计配送位置；
    所述基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员，包括：
    根据每一配送人员的所述预计配送位置与所述每一未分配订单组的起点地址的距离、所述预计配送时间与所述每一未分配订单组的期望送达时间的时间差、对所述每一未分配订单组的起点地址的熟悉程度、对所述每一未分配订单组的终点地址的熟悉程度、配送完成所述每一未分配订单组的预计完成时间、所述每一未分配订单组的紧急程度中的一个或多个因素，计算所述每一未分配订单组与所述每一配送人员的匹配分数；
    根据所述匹配分数，分配所述每一未分配订单组至相匹配的配送人员。
  10. 根据权利要求9所述的方法，其中，所述基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员包括：
    将所述每一未分配订单组分别作为第N个待确定的未分配订单组，执行从未匹配的配送人员中，确定与未匹配的每一未分配订单组匹配程度最高的配送人员的操作，获得M个分配列表；其中，N为未分配订单组的总数量，为大于等于1的整数；M为大于等于1的整数；
    针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；
    按照列表分数最高的分配列表，分配所述每一未分配订单组至对应的配送人员。
  11. 根据权利要求9所述的方法，其中，确定所述配送人员的所述预计配送时间以及所述预计配送位置，包括：
    根据所述配送人员当前未配送完成的已分配订单组，将所述已分配 订单组的预计完成时间作为所述预计配送时间、所述已分配订单组的终点地址作为所述预计配送位置。
  12. 根据权利要求9所述的方法，其中，所述每一配送人员配送完成每一未分配订单组的预计完成时间按照如下方式确定：
    根据所述每一未分配订单组的配送路径、所述每一配送人员的行动速度以及所述每一未分配订单组中每一配送订单的用户等待时间，确定每一配送人员预计完成所述每一配送订单的订单完成时间；
    根据所述订单完成时间，计算所述每一配送人员预计完成所述每一未分配订单组的预计完成时间。
  13. 根据权利要求12所述的方法，其中，基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员之后，还包括：
    针对每一已分配订单组，确定与其相匹配的配送人员预计完成其每一配送订单的订单完成时间；
    将所述每一配送订单的订单完成时间发送至所述每一配送订单对应的寄送方终端或接收方终端。
  14. 根据权利要求5～13任一项所述的方法，还包括：
    基于起点地址之间的距离以及终点地址之间的距离，计算每一配送人员的已分配订单组分别与所述第一配送业务的未分配订单组以及所述第二配送业务未分配的配送订单的订单相似度；
    将订单相似度大于相似阈值的所述第一配送业务的未分配订单组和/或所述第二配送业务未分配的配送订单，加入至所述已分配订单组。
  15. 一种数据处理装置，包括：
    订单获取模块，用于分别获得至少两种配送业务的未分配订单组；
    第一指标确定模块，用于确定配送人员的状态指标；
    第二指标确定模块，用于确定所述未分配订单组的配送指标；
    第一订单分配模块，用于基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
  16. 根据权利要求15所述的装置，其中，所述第一订单分配模块 包括：
    订单确定单元，用于基于所述的配送指标以及所述状态指标，确定与所述未分配订单组相匹配的配送人员；
    订单分配单元，用于响应于任一未分配订单组满足调度条件的判断结果，将所述任一未分配订单组分配至相匹配的配送人员。
  17. 根据权利要求15所述的装置，还包括：
    第二订单分配模块，用于根据起点地址之间的距离以及终点地址之间的距离，将与任一配送人员的已分配订单组相似的未分配订单组加入至所述已分配订单组。
  18. 根据权利要求15所述的装置，其中，所述至少两种配送业务中包括第一配送业务以及第二配送业务。
  19. 根据权利要求15所述的装置，其中，所述至少两种配送业务中包括第一配送业务以及第二配送业务；所述第一配送业务的配送期限大于所述第二配送业务的配送期限；所述第一配送业务与所述第二配送业务的配送高峰期不同；
    所述第一配送业务的配送类型包括从集散点提取配送对象并送达至接收方的派件类型、以及从寄送方提取配送对象并送达至所述集散点的取件类型；
    所述第二配送业务的配送类型为从寄送方接收配送对象并配送至接收方。
  20. 根据权利要求19所述的装置，还包括：
    第一订单划分模块，用于根据所述第一配送业务中未分组的配送订单与集散点地址的距离，选择聚类中心订单；以及
    根据所述未分组的配送订单与所述聚类中心订单的用户地址之间的距离进行聚类处理，以获得所述聚类中心订单对应的未分配订单组。
  21. 根据权利要求19所述的装置，还包括：
    第二订单划分模块，用于确定所述第二配送业务未分配的配送订单的起点地址、终点地址以及期望完成时间；以及
    将起点地址彼此之间的距离在第一距离范围内、终点地址彼此之间 的距离在第二距离范围内、以及期望完成时间彼此之间的时间差位于预设时间范围内的配送订单划分入同一未分配订单组。
  22. 根据权利要求19所述的装置，其中，所述配送指标包括起点地址、终点地址以及期望完成时间；
    所述第一指标确定模块包括：
    第一确定单元，用于针对所述第一配送业务的每一未分配订单组，将所述每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组的期望完成时间；根据每一未分配订单组的各个配送订单的用户地址以及集散点地址，规划各个配送订单的预计配送顺序；针对取件类型，将第一个配送的配送订单的起点地址作为所述每一未分配订单组的起点地址，以及所述集散点地址作为所述每一未分配订单组的终点地址；针对派件类型，将所述集散点地址作为所述每一未分配订单组的起点地址，以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组的终点地址；
    第二确定单元，用于针对所述第二配送业务的每一未分配订单组，将所述每一未分配订单组中各个配送订单的最早期望完成时间作为所述每一未分配订单组对应每一配送人员的期望完成时间；根据每一未分配订单组的各个配送订单的起点地址、终点地址以及所述每一配送人员的预计配送位置，规划各个配送订单对应每一配送人员的预计配送顺序；将第一个配送的配送订单的起点地址作为所述每一未分配订单组对应所述每一配送人员的起点地址、以及最后一个配送的配送订单的终点地址作为所述每一未分配订单组对所述每一配送人员的终点地址。
  23. 根据权利要求22所述的装置，其中，所述配送人员的状态指标包括预计配送时间以及预计配送位置；
    所述第一订单分配模块包括：
    第一计算单元，用于根据每一配送人员的所述预计配送位置与所述每一未分配订单组的起点地址的距离、所述预计配送时间与所述每一未分配订单组的期望送达时间的时间差、对每一未分配订单组的起点地址的熟悉程度、对每一未分配订单组的终点地址的熟悉程度、配送完成每 一未分配订单组的预计完成时间、所述每一未分配订单组的紧急程度中的一个或多个因素，计算所述每一未分配订单组与所述每一配送人员的匹配分数；
    第一订单分配单元，用于根据所述匹配分数，分配所述每一未分配订单组至相匹配的配送人员。
  24. 根据权利要求22所述的装置，其中，所述第一订单分配单元具体用于：将每一未分配订单组分别作为第N个待确定的未分配订单组，执行从未匹配的配送人员中，确定与未确定的每一未分配订单组匹配程度最高的配送人员的操作，获得M个分配列表；其中，N为未分配订单组的总数量，为大于等于1的整数；M为大于等于1的整数；
    针对每一分配列表，计算所述每一未分配订单组对应的匹配分数之和，获得所述每一分配列表的列表分数；
    按照列表分数最优的分配列表，分配所述每一未分配订单组至对应的配送人员。
  25. 根据权利要求23所述的装置，其中，所述第二指标确定模块具体用于：
    根据所述配送人员当前未配送完成的已分配订单组，将所述已分配订单组的预计完成时间作为所述预计配送时间、所述已分配订单组的终点地址作为所述预计配送位置。
  26. 根据权利要求23所述的装置，还包括：
    第一时间确定模块，用于根据每一未分配订单组的配送路径、所述每一配送人员的行动速度以及所述每一未分配订单组中每一配送订单的用户等待时间，确定每一配送人员预计完成每一配送订单的订单完成时间；
    第二时间确定模块，用于根据所述订单完成时间，计算所述每一配送人员预计完成所述每一未分配订单组的预计完成时间。
  27. 根据权利要求26所述的装置，还包括：
    第三时间确定模块，针对每一已分配订单组，确定与其相匹配的配送人员预计完成其每一配送订单的订单完成时间；
    时间提示模块，用于将所述每一配送订单的订单完成时间发送至所述每一配送订单对应的寄送方终端或接收方终端。
  28. 根据权利要求19～27任一项所述的装置，还包括：
    相似度计算模块，用于基于起点地址之间的距离以及终点地址之间的距离，计算每一配送人员的已分配订单组与所述第一配送业务的未分配订单组以及所述第二配送业务未分配的配送订单的订单相似度；
    第三订单分配模块，用于将订单相似度大于相似阈值的所述第一配送业务的未分配订单组和/或所述第二配送业务未分配的配送订单，加入至所述已分配订单组。
  29. 一种数据处理设备，包括处理组件以及存储组件；
    所述存储组件用于存储一条或多条计算机指令，其中，所述一条或多条计算机指令被所述处理组件执行以实现：
    分别获得至少两种配送业务的未分配订单组；
    确定配送人员的状态指标；
    确定所述未分配订单组的配送指标；
    基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
  30. 一种计算机可读存储介质，其上存储有计算机指令，该计算机指令被处理器执行时实现以下步骤：
    分别获得至少两种配送业务的未分配订单组；
    确定配送人员的状态指标；
    确定所述未分配订单组的配送指标；
    基于所述配送指标以及所述状态指标，分配所述未分配订单组至相匹配的配送人员。
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