WO2022206323A1 - 调度方法、装置、电子设备及存储介质 - Google Patents

调度方法、装置、电子设备及存储介质 Download PDF

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Publication number
WO2022206323A1
WO2022206323A1 PCT/CN2022/079956 CN2022079956W WO2022206323A1 WO 2022206323 A1 WO2022206323 A1 WO 2022206323A1 CN 2022079956 W CN2022079956 W CN 2022079956W WO 2022206323 A1 WO2022206323 A1 WO 2022206323A1
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delivery
order
grouping
orders
optimal
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PCT/CN2022/079956
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English (en)
French (fr)
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冯子鹤
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北京沃东天骏信息技术有限公司
北京京东世纪贸易有限公司
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Publication of WO2022206323A1 publication Critical patent/WO2022206323A1/zh

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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
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • 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 present application relates to the technical field of warehousing and logistics, and in particular, to a scheduling method, device, electronic device and storage medium.
  • the courier in order to improve the efficiency of the distribution order, the courier usually matches multiple orders along the way according to their own experience. However, due to the limited experience of the delivery staff, the matched orders are not smooth, and the efficiency of delivery orders cannot be effectively improved.
  • the embodiments of the present application provide a scheduling method, an apparatus, an electronic device, and a storage medium.
  • the embodiment of the present application provides a scheduling method, including:
  • each grouping method is used to divide the multiple orders to be delivered into at least one order group; each order group contains at least one Order;
  • the optimal grouping method is determined from the multiple grouping methods; the number of order groups in the optimal grouping method is the least among the multiple grouping methods, and the delivery time of the optimal grouping method is the least among the multiple grouping methods.
  • grouped delivery is performed on the multiple orders to be delivered.
  • the determining of multiple grouping methods for the multiple orders to be delivered includes:
  • the first threshold Based on the first threshold and the agreed arrival time of each to-be-delivered order among the multiple to-be-delivered orders, determine multiple grouping methods for the multiple to-be-delivered orders; wherein, based on each grouping method, the multiple When the orders to be delivered are grouped and delivered, the time when each order arrives at the destination does not exceed the corresponding agreed arrival time, and the number of orders contained in each order group of each grouping method is less than or equal to the first threshold.
  • determining the optimal grouping method from the multiple grouping methods includes:
  • the grouping method with the shortest delivery duration among the at least two grouping methods is determined as the optimal grouping method.
  • the method also includes:
  • each grouping method use the route optimization strategy to determine the optimal delivery path of each order group in the corresponding grouping method; and determine the delivery time of the corresponding grouping method based on the determined optimal delivery path for each order group;
  • the optimal grouping manner is determined from the plurality of grouping manners.
  • the optimal distribution route for each order group in the corresponding grouping method is determined by using the route optimization strategy, including:
  • At least one delivery route of the corresponding order group is determined; and an optimal delivery route is determined from the at least one delivery route; wherein, the delivery duration of the optimal delivery route is in the The at least one delivery route is the shortest.
  • the method also includes:
  • the first information includes the destination coordinates of each order included in the corresponding order group; the second information includes a reserved duration set for unexpected delivery situations; the The third information includes the order delivery speed.
  • the method also includes:
  • the second information and the third information are determined.
  • grouping and delivering the multiple orders to be delivered includes:
  • the method also includes:
  • Monitor the status switching operation of the delivery staff update the status of the delivery staff based on the monitored status switching operation of the delivery staff; the status of the delivery staff at least includes the unchecked status, the status of waiting in line, the status of waiting for orders, the status of delivery and the rest state.
  • For each order group in the optimal grouping method determine the delivery time of the corresponding order group; determine the start delivery time of the corresponding order group based on the delivery time of the corresponding order group; determine whether the current time reaches the start delivery time; When the current time reaches the delivery start time, all orders included in the corresponding order group are allocated to the same delivery staff in the order-waiting state for delivery.
  • the method also includes:
  • the embodiment of the present application also provides a scheduling device, including:
  • an acquisition unit configured to acquire multiple orders to be delivered
  • a first processing unit configured to determine multiple grouping methods for the multiple orders to be delivered; each grouping method is used to divide the multiple orders to be delivered into at least one order group; each order group contains at least one Order;
  • the second processing unit is configured to determine an optimal grouping method from the multiple grouping methods; the number of order groups in the optimal grouping method is the least among the multiple grouping methods, and the optimal grouping method
  • the delivery time is the shortest among the various grouping methods
  • the third processing unit is configured to perform group distribution on the plurality of orders to be distributed based on the optimal grouping manner.
  • Embodiments of the present application further provide an electronic device, including: a processor and a memory configured to store a computer program that can be executed on the processor;
  • the processor is configured to execute the steps of any of the above methods when running the computer program.
  • Embodiments of the present application further provide a storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the steps of any of the foregoing methods.
  • the scheduling method, device, electronic device, and storage medium acquire multiple orders to be delivered; determine multiple grouping methods for the multiple orders to be delivered;
  • the orders to be delivered are divided into at least one order group; each order group contains at least one order;
  • the optimal grouping method is determined from the multiple grouping methods; the number of order groups in the optimal grouping method is among the multiple grouping methods.
  • the grouping method is the least, and the delivery time of the optimal grouping method is the shortest among the multiple grouping methods; based on the optimal grouping method, the multiple orders to be delivered are grouped and delivered.
  • the solution of the embodiment of the present application determines the optimal grouping method with the smallest number of order groups and the shortest delivery time from the various grouping methods for multiple orders to be delivered, and performs a grouping method on the multiple orders to be delivered based on the optimal grouping method.
  • Group distribution in this way, automatic scheduling of order distribution can be realized, that is, matching drop-in orders (that is, orders included in an order group) are automatically allocated to the courier, so that the courier can deliver as much as possible in the shortest possible time.
  • matching drop-in orders that is, orders included in an order group
  • the courier can deliver as much as possible in the shortest possible time.
  • FIG. 1 is a schematic flowchart of a scheduling method according to an embodiment of the present application
  • FIG. 2 is a schematic diagram of state flow of a courier according to an application embodiment of the present application
  • FIG. 3 is a schematic diagram of another courier state flow diagram according to an application embodiment of the present application.
  • FIG. 4 is a schematic diagram of an automatic assignment process of a system in an application embodiment of the present application.
  • FIG. 5 is a schematic flow chart of an order from payment to delivery completion of an application embodiment of the present application.
  • FIG. 6 is a schematic diagram of the delivery duration of a collection order according to an application embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of a scheduling apparatus according to an embodiment of the present application.
  • FIG. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • delivery staff in order to improve the efficiency of delivery orders, delivery staff usually can only rely on their own experience to match orders along the way. For new recruits or delivery staff who are unfamiliar with road conditions, it is difficult to match orders along the way. There are cases where the road is not right, and it is impossible to accurately judge the order of delivery. Therefore, the training cost of the delivery staff is relatively large, and the delivery efficiency of the order is relatively low, resulting in a poor user experience.
  • the delivery staff will blindly wait for orders on the spot, resulting in a waste of delivery time; , orders with short delivery distance), resulting in waste of management costs (such as store management costs), making management costs higher.
  • the delivery staff usually scan codes spontaneously to receive orders and cannot receive automatically assigned tasks. In other words , the distribution scheduling of the order is realized manually, and the management cost is high. For example, when an offline retailer has an after-sales order in a super-store, the store administrator needs to manually assign the after-sales order according to the location and status of the courier.
  • the optimal grouping method with the smallest number of order groups and the shortest delivery time is determined from the various grouping methods for multiple orders to be delivered, and based on the optimal grouping method Multiple orders to be delivered are grouped for delivery; in this way, the automatic scheduling of order delivery can be realized, that is, the matched drop-in orders (that is, the orders included in an order group) are automatically allocated to the delivery staff, so that the delivery staff can be dispatched within the shortest possible time. Deliver as many orders as possible within time, and at the same time, there is no need for delivery staff to match orders based on their own experience, and the matched orders will not be out of the way, which can effectively improve the efficiency of delivery orders. After the delivery efficiency of the order is improved, the time-out of order delivery can be reduced, thereby improving the user experience.
  • An embodiment of the present application provides a scheduling method, which is applied to an electronic device (such as a server). As shown in FIG. 1 , the method includes:
  • Step 101 Acquire multiple orders to be delivered; determine multiple grouping methods for the multiple orders to be delivered;
  • each grouping manner is used to divide the multiple orders to be delivered into at least one order group; each order group contains at least one order;
  • Step 102 Determine the optimal grouping method from the multiple grouping methods
  • the number of order groups in the optimal grouping method is the least among the multiple grouping methods, and the delivery time of the optimal grouping method is the shortest among the multiple grouping methods;
  • Step 103 Based on the optimal grouping manner, grouping and delivering the multiple orders to be delivered.
  • the manner in which the electronic device obtains the order to be delivered may be set according to requirements.
  • the electronic device may acquire orders to be delivered from a local order pool, and the orders in the local order pool may be orders received by the electronic device from other electronic devices (such as clients); for another example, the The electronic device may acquire the order to be delivered from the other electronic device by sending an order request message to the other electronic device (such as another server) and receiving the order message returned by the other electronic device.
  • the number of orders contained in an order group should not exceed the delivery capacity of the delivery staff.
  • the determining of multiple grouping manners for the multiple orders to be delivered may include:
  • each order group of each grouping method contains an order number of The number is less than or equal to the first threshold.
  • each determined grouping method needs to meet the following two conditions at the same time:
  • the time when each order arrives at the destination does not exceed the corresponding agreed arrival time (which can be recorded as the first condition in the subsequent description);
  • the number of orders contained in each order group of the corresponding grouping method is less than or equal to the first threshold (which may be referred to as the second condition in the subsequent description).
  • the determining of multiple grouping methods for the multiple orders to be delivered can be understood as: based on the first threshold and the agreed arrival time of each of the multiple orders to be delivered, Identify multiple groupings that satisfy the first condition and the second condition.
  • the path optimization strategy can be used to determine each of the candidate grouping methods.
  • the optimal distribution path of the order group and based on the determined optimal distribution path of each order group and the current moment, using the first information, the second information and the third information, determine the destination of each order included in the corresponding order group Whether the time exceeds the corresponding agreed arrival time.
  • the first information includes the destination coordinates of each order included in the corresponding order group; the second information includes the reserved duration (for example, 5 minutes) set for unexpected delivery situations; the third information includes the order Delivery speed.
  • the route can be understood as the order of delivery of orders, and the basic idea of the route optimization strategy is: in at least one delivery route for an order group, the delivery time of the optimal delivery route is the shortest.
  • the first information, the second information and the third information may also be used to determine the delivery time of each delivery route.
  • the electronic device may acquire historical delivery data related to historical orders from a local or other electronic device, and use the acquired historical delivery data to determine the second information and the third information.
  • the historical delivery data may include the origination time of the historical order, the agreed arrival time of the historical order, the coordinates of the starting place for delivery of the historical order, the starting delivery time of the historical order, the destination coordinates of the historical order, the arrival time of the historical order, and the calling user.
  • the number and duration of the delivery process, the length of stay in the delivery process for example, stop due to signal lights or stop for walking delivery, pickup and loading, etc.
  • the delivery staff of historical orders for example, stop due to signal lights or stop for walking delivery, pickup and loading, etc.
  • the method may further include:
  • the second information and the third information are determined.
  • the second information may include at least one of the following:
  • the reserved time (such as 3 minutes) set for walking delivery; specifically, the order destination may be on a higher floor or there may be no elevator, and the delivery person needs to climb the stairs for delivery. Therefore, in order to ensure that the order can be delivered on time, it is necessary to set Reserve time.
  • the reservation time set for the contact user (for example, 1 minute); specifically, the user may be inconvenient to answer the phone, and the delivery person needs to call multiple times. Therefore, in order to ensure that the order can be delivered on time, the reservation time needs to be set.
  • the reserved time (for example, 3 minutes) is set for the pickup and loading situation. Specifically, after the order is allocated to the delivery staff, the delivery staff needs to pick up the corresponding goods. Therefore, in order to ensure that the order can be delivered on time, the reserved time needs to be set.
  • the reserved time (for example, 3 minutes) is set for the situation where there are many signal lights; specifically, when the number of signal lights is greater than the second threshold (which can be set according to requirements), it can be determined that there are more signal lights. In order to ensure that the order can be delivered on time, it needs to be set Reserve time.
  • the first threshold may be set according to the delivery capability of the delivery person, for example, 3.
  • the delivery capability of the delivery staff can also be determined by using the historical delivery data.
  • step 102 the optimal grouping method needs to satisfy the following two conditions:
  • the number of order groups in the optimal grouping method is the least among the multiple grouping methods (it can be recorded as the third condition in the subsequent description);
  • the delivery duration of the optimal grouping method is the shortest among the multiple grouping methods (which may be referred to as the fourth condition in the subsequent description).
  • determining the optimal grouping manner from the multiple grouping manners may be understood as: determining the optimum grouping manner that satisfies the third condition and the fourth condition from the multiple grouping manners.
  • the fewer the number of order groups the more orders each order group contains.
  • the judgment priority of the third condition may be higher than the judgment priority of the fourth condition.
  • the judgment priority of the third condition is higher than the judgment priority of the fourth condition, which can be understood as: among the multiple grouping methods, the grouping method with the smallest number of order groups and the grouping method with the shortest delivery time
  • the grouping method that satisfies the third condition among the multiple grouping methods may be determined first, and in the case that only one grouping method satisfies the third condition, the grouping method that satisfies the third condition is grouped.
  • the optimal grouping method is determined as the optimal grouping method; when there are at least two grouping methods that satisfy the third condition, the grouping method that satisfies the fourth condition among the at least two grouping methods that satisfy the third condition is determined as The optimal grouping method, in other words, the grouping method with the shortest delivery time among the at least two grouping methods satisfying the third condition is determined as the optimal grouping method.
  • the determining an optimal grouping manner from the multiple grouping manners may include:
  • the grouping method with the shortest delivery duration among the at least two grouping methods is determined as the optimal grouping method.
  • the delivery time of each grouping method needs to be determined.
  • the method may further include:
  • each grouping method using the route optimization strategy, determine the optimal delivery route of each order group in the corresponding grouping method; and determine the delivery time length of the corresponding grouping method based on the determined optimal delivery route for each order group;
  • the determining the optimal grouping manner from the multiple grouping manners may include:
  • the optimal grouping manner is determined from the plurality of grouping manners.
  • determining the optimal delivery route for each order group in a corresponding grouping manner by using the route optimization strategy may include:
  • At least one delivery route of the corresponding order group is determined; and an optimal delivery route is determined from the at least one delivery route; wherein, the delivery duration of the optimal delivery route is in the The at least one delivery route is the shortest.
  • the delivery time of each delivery route needs to be determined.
  • the method may further include:
  • the determining the optimal delivery route from the at least one delivery route may include:
  • an optimal delivery route is determined from the at least one delivery route.
  • the grouped distribution of the plurality of orders to be distributed based on the optimal grouping method may include:
  • allocating all the orders included in the corresponding order group to the same deliveryman in the order-waiting state for delivery may include: the electronic device sending the relevant information of all the orders included in the corresponding order group to a delivery person.
  • the itinerary and status of the delivery staff can be monitored to achieve refined management of the delivery staff.
  • the electronic device can monitor the itinerary of the delivery staff by acquiring the location of the delivery staff in real time from the terminal held by the delivery staff, and determine whether the delivery staff is in a delivery state according to the acquired position.
  • the delivery staff may also perform a state switching operation through the terminal they hold to switch their own states.
  • the method may further include:
  • Monitor the status switching operation of the delivery staff update the status of the delivery staff based on the monitored status switching operation of the delivery staff; the status of the delivery staff at least includes the unchecked status (also referred to as the status to be checked in), the status of waiting to be queued, Pending order status (also known as queuing status), delivery status (also known as delivery status) and rest status.
  • unchecked status also referred to as the status to be checked in
  • Pending order status also known as queuing status
  • delivery status also known as delivery status
  • rest status rest status.
  • the electronic device can monitor the state switching operation of the delivery person by receiving the message sent by the terminal held by the delivery person.
  • the terminal may send a login message to the electronic device, and after the electronic device receives the login message, it may determine that the delivery person is an unauthorized delivery person. check-in status, and send a non-check-in status indication message to the terminal to instruct the terminal to present a non-check-in status in the delivery system.
  • the delivery person can click the sign-in button in the delivery system to trigger the terminal to send a sign-in message to the electronic device.
  • the electronic device After the electronic device receives the sign-in message, it can determine that the delivery person is in a waiting state, and report to the electronic device.
  • the terminal sends a waiting-to-queue state indication message to instruct the terminal to present a waiting-to-queue state in the delivery system.
  • the delivery person can click the delivery completion button in the delivery system to trigger the terminal to send a delivery completion message to the electronic device, and after the electronic device receives the delivery completion message, It may be determined that the delivery person is in a waiting-to-queue state, and a waiting-to-queue state indication message is sent to the terminal to indicate that the terminal is in a waiting-to-queue state in the delivery system.
  • the delivery person determines that he can deliver the order
  • he can click the queuing button in the delivery system to trigger the terminal to send a queuing message to the electronic device.
  • the electronic device After receiving the queuing message, the electronic device can determine the queue.
  • the delivery person is in the order-waiting state, and sends an order-waiting state indication message to the terminal to instruct the terminal to present the order-waiting state in the delivery system.
  • the delivery person can click the order button in the delivery system to trigger the terminal to send the order to the delivery system.
  • the electronic device sends an order receiving message.
  • the electronic device can determine that the delivery person is in the delivery state, and send a delivery status indication message to the terminal to indicate that the terminal is in the delivery system. Show delivery status.
  • the delivery person can click the rest button in the delivery system when he needs to rest, and trigger the terminal to send a rest message to the electronic device.
  • the electronic device can determine that the delivery person is in a rest state, and A rest state indication message is sent to the terminal to instruct the terminal to present a rest state in the delivery system.
  • the status of the delivery staff may also include a signed-out status
  • the delivery staff can click the check-out button in the delivery system when off-duty to trigger the terminal to send a check-out message to the electronic device, so After receiving the sign-out message, the electronic device can determine that the delivery person is in the sign-out state, and send a sign-out status indication message to the terminal to instruct the terminal to present the sign-out state in the delivery system.
  • ungrouped orders to be delivered may continue to increase. If only a certain number of orders are accumulated and then grouped for delivery, it may cause some orders to time out. Under the premise of time-out, the delivery start time of each order group in the optimal grouping method, and when the current moment reaches the start delivery time of the corresponding order group, all the orders included in the corresponding order group are allocated to the same one at the same time. The delivery staff in the pending order status will deliver.
  • allocating all the orders included in the corresponding order group to the same deliveryman in the order-waiting state for delivery may include:
  • For each order group in the optimal grouping method determine the delivery time of the corresponding order group; determine the start delivery time of the corresponding order group based on the delivery time of the corresponding order group; determine whether the current time reaches the start delivery time; When the current time reaches the delivery start time, all orders included in the corresponding order group are allocated to the same delivery staff in the order-waiting state for delivery.
  • the route optimization strategy may be used first to determine the optimal delivery route of the corresponding order group, and then the first information, the second information and the third information may be used to determine the optimal delivery route.
  • the delivery duration of the optimal delivery route (that is, the delivery duration of the corresponding order group).
  • the method may further include:
  • all the orders to be delivered that are not currently assigned to the delivery staff are dynamically changed, and all the orders to be delivered include the acquired at least one new order to be delivered, and the delivery start time has not been reached during the last group delivery process.
  • the orders contained in the order group are dynamically changed, and all the orders to be delivered include the acquired at least one new order to be delivered, and the delivery start time has not been reached during the last group delivery process.
  • the electronic device can send all orders included in the corresponding order group when the delivery start moment is reached. It is assigned to the same delivery person in the pending order status for delivery.
  • allocating all the orders included in the corresponding order group to the same deliveryman in the order-waiting state for delivery may include:
  • multiple orders to be delivered are acquired; multiple grouping methods for the multiple orders to be delivered are determined; each grouping method is used to divide the multiple orders to be delivered into at least one order Each order group contains at least one order; the optimal grouping method is determined from the multiple grouping methods; the number of order groups in the optimal grouping method is the least among the multiple grouping methods, and the The delivery duration of the optimal grouping method is the shortest among the multiple grouping methods; based on the optimal grouping method, the multiple orders to be delivered are grouped and delivered.
  • the solution of the embodiment of the present application determines the optimal grouping method with the smallest number of order groups and the shortest delivery time from the various grouping methods for multiple orders to be delivered, and performs a grouping method on the multiple orders to be delivered based on the optimal grouping method.
  • Group distribution in this way, automatic scheduling of order distribution can be realized, that is, matching drop-in orders (that is, orders included in an order group) are automatically allocated to the courier, so that the courier can deliver as much as possible in the shortest possible time.
  • matching drop-in orders that is, orders included in an order group
  • the courier can deliver as much as possible in the shortest possible time.
  • the time-out of order delivery can be reduced, thereby improving the user experience.
  • the order group is called a collection order, which includes all orders assigned to the delivery staff at one time; the number of orders included in the collection order is called the collection order number, that is, the number of all orders allocated to the delivery staff at one time;
  • the first threshold is called the upper limit of the order collection, which is determined according to the ability of the courier; all the order groups in the optimal grouping method are called the optimal order combination; the courier is called the courier.
  • the itinerary of the courier is monitored, and the state of the courier is managed in a refined manner.
  • the optimal order combination and route planning are calculated to realize the automatic order assignment function, and avoid the courier matching orders based on experience, blindly waiting for orders, picking orders and the phenomenon of order grabbing.
  • the latest delivery time refers to the latest departure time when the courier is not late after the order is assigned to the courier.
  • FIG. 2 and FIG. 3 show the courier state flow process. The following describes the solution for managing the courier state in this application embodiment with reference to FIG. 2 and FIG. 3 .
  • the courier includes the following states:
  • the courier switches to the queued status after clicking sign-in in the delivery system or after the order delivery is completed (the order status can be delivered or rejected);
  • Queued status i.e. pending order status
  • the courier switches to queued status after clicking queue in the delivery system
  • Delivery status the courier automatically switches to delivery status after receiving the order
  • the refined management of the courier is realized through the above six courier states.
  • a model of automatic order assignment algorithm is established, and a distribution system is constructed based on the established algorithm model.
  • FIG. 4 shows the flow of the distribution system automatically assigning orders, and the functions of the distribution system are described below with reference to FIG. 4 .
  • the delivery system includes:
  • the production module is configured to pick and pack the goods corresponding to the order.
  • the order from payment to delivery includes the following processes: order generation, waiting for payment, paid, picking, picking, starting to pack, packing, picking and delivery (including delivery and Reject); the pick pool includes all orders in the pick, and the pack pool includes the used orders in the pack.
  • the algorithm module is configured to calculate the optimal set-single combination.
  • the algorithm module includes a data analysis module and a calculation module; the data analysis module is configured to analyze basic data, and the basic data may include relevant data of orders to be delivered and relevant data of historical orders (that is, the above historical order-related historical shipping data).
  • the calculating module is configured to calculate the latest delivery time of the order-collection combination, and calculate the optimal order-collection combination.
  • the delivery module is configured to receive the optimal collection order combination given by the algorithm module, and assign each collection order of the optimal collection order combination to the courier in the queuing state.
  • the courier can scan the code in the store to receive the order through the terminal.
  • the courier can start the delivery.
  • the courier can switch back to the queued state, and by clicking Queue on the terminal, switch to the queued state and continue Receive the collection order assigned by the distribution system.
  • the store owner can assist the distribution system to pull the courier back to complete the order.
  • the data parsing module starts parsing the basic data.
  • the process of analyzing the basic data by the data analysis module can be understood as data preprocessing.
  • data preprocessing can include the following steps:
  • Step 1 Convert the coordinates for the delivery address (ie, destination) of each order, that is, convert the text address into latitude and longitude coordinates, and record (ie, store) the converted coordinates.
  • Step 2 Calculate each order according to the courier's positioning information (such as the time the courier arrives at the gate of the community and the time the courier arrives at the delivery destination) in the relevant data of the historical order (that is, the historical distribution data related to the above historical order)
  • the duration of climbing stairs and making phone calls (referred to as the single-point service duration in the subsequent description).
  • Step 3 According to the courier's positioning information in the relevant data of historical orders (such as the time the courier arrives at the store and the time when the courier leaves the store), calculate the time required for the courier to pick up and load the goods for each delivery (in the following description). Recorded as the buffer (BUFFER) duration).
  • the above-mentioned reserved duration (ie, the above-mentioned second information) set for the delivery emergency includes the single-point service duration and the BUFFER duration.
  • Step 4 Calculate the riding speed of each delivery road area according to the courier's positioning information in the relevant data of historical orders (such as the time the courier leaves the store and the time when the courier arrives at the delivery destination), that is, the above order delivery speed (Third Information).
  • the delivery road area can be divided according to demand.
  • Step 5 For all orders in the picking pool, make a sufficient combination between every two orders, in other words, determine any two orders in all the orders in the picking pool as a collection order, and obtain multiple collections According to the destination coordinates of each order in each collection order, call the preset map module to determine the navigation distance of each collection order, calculate the riding time of the courier, and record (ie, store) it in the algorithm model.
  • the calculation module calculates the optimal order combination.
  • the calculation module calculates the optimal set-single combination, it needs to follow the set-single rule and the optimal selection rule.
  • order collection logic when an order enters the packaging pool, each order in the packaging pool can be fully fulfilled (that is, the first condition above, the order is delivered before the agreed arrival time) , and under the premise that the number of orders is less than or equal to the upper limit of the order collection (that is, the second condition above), the order collection is carried out with the latest departure delivery time as the deadline for order collection time (that is, the real-time determination of all orders in the packaging pool. multiple groupings).
  • the latest delivery time of a collection order may be equal to the user's expected delivery time (ie, the above-mentioned agreed arrival time) - the total journey time required to reach the order destination - the single-point service time - the BUFFER time.
  • the total journey time required to reach the destination of the order is the shortest when delivery is carried out according to the path of order A-order B-order C, 40 minutes, the expected delivery time of order C is 9:00, the single-point service time and the BUFFER time are both 3 minutes; at this time, it can be determined that the latest departure time for the collective order is 8:08 (9: 00 - 40 minutes - 9 minutes (3 x 3 minutes) - 3 minutes).
  • the computing module will first calculate the latest delivery time for order D to leave the store (assuming it is 9:10).
  • order D can also wait for matching for another 10 minutes, and after waiting for 10 minutes If no new order enters the packing pool, or the new order entering the packing pool cannot be matched with order D (that is, the two orders cannot form a collective order because the new order and/or order D will be delivered overtime), delivery
  • the system can directly assign the order D to the courier for delivery (that is, the computing module can directly send the order D to the delivery module as the optimal order combination). If order E enters the packing pool within 10 minutes, and order E can match with order D (that is, order E and order D can form a collective order without the delivery time-out), the computing module will calculate the order D and order D and order D.
  • the optimal delivery route for order E that is, to calculate the delivery time required to deliver order D first and then order E, and the delivery time required to deliver order E first and then order D, and compare which route has the shortest delivery time; assuming the calculation module It is calculated that the delivery time required to deliver order D first and then order E is the shortest, the latest departure delivery time corresponding to the optimal delivery route is 9:08, and the current time is 9:05, then order D and order E at this time You can wait for another 3 minutes to match. In the case that no new orders enter the packing pool after waiting for 3 minutes, or the new orders entering the packing pool cannot be matched with order D and/or order E, the delivery system can use order D and order E as the optimal order combination Contains a collection order assigned to a courier for delivery.
  • the calculation module will calculate the optimal delivery path between order D, order E and order F, that is, in " Order D—Order E—Order F”, “Order D—Order F—Order E”, “Order E—Order D—Order F”, “Order E—Order F—Order D”, “Order F—Order D— Among the six delivery routes of "Order E” and "Order F-Order E-Order D”, determine the optimal delivery route with the shortest delivery time, and calculate the latest departure delivery time corresponding to the optimal delivery route, and if there is still waiting time (that is, if the current time has not reached the latest delivery time for leaving the store), continue to wait for new orders to enter the packaging pool and perform order matching; if there is no waiting time (that is, the current time reaches the latest delivery time for leaving the store),
  • the delivery system can assign order D, order E and order F as a collection order included in the optimal collection
  • the basic idea of the optimal selection rule is: for a variety of order grouping methods determined according to the basic idea of the collection order rule (each order can be fulfilled, and the collection order number of each collection order is less than or equal to the upper limit of the collection order) ), sort the order grouping methods from small to large according to the number of sets of order grouping methods (the smaller the number of sets, the larger the number of sets, that is, the more orders the courier can deliver at one time); and according to the order grouping method According to the required delivery time, various order grouping methods are sorted from small to large; according to the sorting results of the two order grouping methods, the optimal grouping method is determined, that is, the optimal order combination is obtained.
  • the order grouping method with the smallest number of aggregates (that is, the third condition above) is the first priority
  • the order grouping method with the shortest delivery time (that is, the fourth condition above) is the first priority.
  • Second priority in the case where the order grouping method with the smallest aggregate number is different from the order grouping method with the shortest delivery time, the order grouping method with the smallest aggregate number is determined as the optimal grouping method; the order grouping method with the smallest aggregate number is the optimal grouping method; If the method is the same as the order grouping method with the shortest delivery time, the order grouping method that satisfies both conditions at the same time is determined as the optimal grouping method, and the optimal collection order combination is obtained.
  • the collection order at the out-of-store delivery time is assigned to the courier in the queued state.
  • Combination 1 set order 1 (order G, order H and order I) and set order 2 (order J and order K);
  • Combination 2 set order 3 (order G and order H) and set order 4 (order I, order J and order K);
  • Combination 3 Collection Order 5 (Order G and Order H), Collection Order 6 (Order I) and Collection Order 7 (Order J and Order K);
  • combination 2 is the optimal grouping method, that is, it can be determined that set single 3 and set single 4 are the optimal set single combination.
  • the collection order 4 (order I, order J and order K) can be directly assigned to the courier in the queue.
  • the solution provided by this application example finely monitors the delivery status of the courier, builds the algorithm logic for automatic order assignment, and performs path planning for the collection order; in this way, the efficiency of the delivery order can be effectively improved, and the user experience.
  • the embodiment of the present application further provides a scheduling apparatus, as shown in FIG. 7 , the apparatus includes:
  • Obtaining unit 701 configured to obtain multiple orders to be delivered
  • the first processing unit 702 is configured to determine multiple grouping methods for the multiple orders to be delivered; each grouping method is used to divide the multiple orders to be delivered into at least one order group; each order group contains at least one order group. an order;
  • the second processing unit 703 is configured to determine an optimal grouping method from the multiple grouping methods; the number of order groups in the optimal grouping method is the least among the multiple grouping methods, and the optimal grouping method has the least number of order groups.
  • the delivery time of the method is the shortest among the multiple grouping methods;
  • the third processing unit 704 is configured to, based on the optimal grouping manner, perform grouping and delivery on the multiple orders to be delivered.
  • the first processing unit 702 is configured to, based on a first threshold and the agreed arrival time of each order to be delivered in the plurality of orders to be delivered, determine the order to be delivered for the plurality of orders to be delivered multiple grouping methods; wherein, when the multiple orders to be delivered are grouped and distributed based on each grouping method, the time when each order arrives at the destination does not exceed the corresponding agreed arrival time, and each grouping method The number of orders contained in the order group is less than or equal to the first threshold.
  • the second processing unit 703 is configured as:
  • the grouping method with the shortest delivery duration among the at least two grouping methods is determined as the optimal grouping method.
  • the second processing unit 703 is configured as:
  • each grouping method use the route optimization strategy to determine the optimal delivery path of each order group in the corresponding grouping method; and determine the delivery time of the corresponding grouping method based on the determined optimal delivery path for each order group;
  • the optimal grouping manner is determined from the plurality of grouping manners.
  • the second processing unit 703 is configured to, for each order group in the corresponding grouping manner, determine at least one delivery route of the corresponding order group; and determine the optimal delivery route from the at least one delivery route.
  • the second processing unit 703 is configured to, for each order group in the corresponding grouping manner, use the first information, the second information and the third information to determine the delivery of each delivery route of the corresponding order group. and determining the optimal delivery route from the at least one delivery route based on the delivery duration of each delivery route; wherein the first information includes the destination coordinates of each order included in the corresponding order group; the The second information includes the reserved duration set for delivery emergencies; the third information includes the order delivery speed.
  • the obtaining unit 701 is configured to obtain historical delivery data related to historical orders
  • the second processing unit 703 is configured to use the acquired historical delivery data to determine the second information and the third information.
  • the third processing unit 704 is configured to, for each order group in the optimal grouping manner, assign all the orders included in the corresponding order group to the same deliveryman in the order-waiting state. delivery.
  • the device further includes a monitoring unit configured to monitor the status switching operation of the delivery staff; based on the monitored status switching operation of the delivery staff, update the status of the delivery staff; the status of the delivery staff at least includes not checking in. Status, queued status, pending order status, delivery status, and rest status.
  • the third processing unit 704 is configured to, for each order group in the optimal grouping manner, determine the delivery duration of the corresponding order group; and determine the delivery duration of the corresponding order group based on the delivery duration of the corresponding order group. Start delivery time; determine whether the current time reaches the start delivery time; in the case that the current time reaches the start delivery time, assign all orders included in the corresponding order group to the same delivery staff in the order-waiting state for delivery .
  • the obtaining unit 701 is configured to obtain at least one new order to be delivered when the current moment does not reach the start delivery moment;
  • the first processing unit 702 is configured to re-determine multiple grouping methods for all orders to be delivered that are not currently allocated to delivery staff;
  • the second processing unit 703 is configured to determine a new optimal grouping manner from the re-determined multiple grouping manners
  • the third processing unit 704 is configured to, based on the new optimal grouping method, perform grouped delivery for all the orders to be delivered that are not currently allocated to delivery staff.
  • the third processing unit 704 is configured to assign all the orders included in the corresponding order group to the same pending order when the acquiring unit 701 does not acquire a new order to be delivered. The courier in the status will make the delivery.
  • the acquisition unit 701 and the monitoring unit can be implemented by the processor in the device in combination with the communication interface; the first processing unit 702, the second processing unit 703 and the third processing unit 704 can be implemented by The processor in the device is implemented.
  • the scheduling device provided in the above embodiment performs distribution scheduling
  • only the division of the above-mentioned program modules is used as an example for illustration.
  • the above-mentioned processing can be allocated to different program modules according to needs.
  • the internal structure of the device is divided into different program modules to complete all or part of the processing described above.
  • the scheduling apparatus and the scheduling method embodiments provided by the above embodiments belong to the same concept, and the specific implementation process thereof is detailed in the method embodiments, which will not be repeated here.
  • the embodiments of the present application further provide an electronic device.
  • the electronic device 800 includes:
  • the processor 802 is connected to the communication interface 801 to realize information interaction with other electronic devices, and is configured to execute the method provided by one or more of the above technical solutions when running a computer program;
  • the memory 803 stores computer programs that can run on the processor 802 .
  • the processor 802 is configured as:
  • each grouping method is used to divide the multiple orders to be delivered into at least one order group; each order group contains at least one Order;
  • the optimal grouping method is determined from the multiple grouping methods; the number of order groups in the optimal grouping method is the least among the multiple grouping methods, and the delivery time of the optimal grouping method is the least among the multiple grouping methods.
  • grouped delivery is performed on the multiple orders to be delivered.
  • the processor 802 is configured to, based on the first threshold and the agreed arrival time of each order to be delivered in the plurality of orders to be delivered, determine the number of orders for the plurality of orders to be delivered A grouping method; wherein, when the multiple orders to be delivered are grouped and distributed based on each grouping method, the time when each order arrives at the destination does not exceed the corresponding agreed arrival time, and each order group in each grouping method The number of included orders is less than or equal to the first threshold.
  • the processor 802 is configured to:
  • the grouping method with the shortest delivery duration among the at least two grouping methods is determined as the optimal grouping method.
  • the processor 802 is configured to:
  • each grouping method use the route optimization strategy to determine the optimal delivery path of each order group in the corresponding grouping method; and determine the delivery time of the corresponding grouping method based on the determined optimal delivery path for each order group;
  • the optimal grouping manner is determined from the plurality of grouping manners.
  • the processor 802 is configured to, for each order group in the corresponding grouping manner, determine at least one delivery route of the corresponding order group; and determine the optimal delivery route from the at least one delivery route. ; wherein, the delivery duration of the optimal delivery route is the shortest in the at least one delivery route.
  • the processor 802 is configured to, for each order group in the corresponding grouping manner, use the first information, the second information and the third information to determine the delivery duration of each delivery route of the corresponding order group; And based on the delivery time of each delivery route, the optimal delivery route is determined from the at least one delivery route; wherein, the first information includes the destination coordinates of each order included in the corresponding order group; the second The information includes the reserved duration set for delivery emergencies; the third information includes the order delivery speed.
  • the processor 802 is configured to:
  • the second information and the third information are determined.
  • the processor 802 is configured to, for each order group in the optimal grouping manner, assign all the orders included in the corresponding order group to the same deliveryman in the order-waiting state for delivery.
  • the processor 802 is configured to monitor the state switching operation of the delivery staff; based on the monitored state switching operation of the delivery staff, update the status of the delivery staff; the status of the delivery staff at least includes an unchecked state. , pending queue status, pending order status, delivery status and rest status.
  • the processor 802 is configured to, for each order group in the optimal grouping manner, determine the delivery duration of the corresponding order group; based on the delivery duration of the corresponding order group, determine the start delivery of the corresponding order group. time; determine whether the current time reaches the start delivery time; in the case that the current time reaches the start delivery time, assign all orders included in the corresponding order group to the same deliveryman in the order-waiting state for delivery.
  • the processor 802 is configured to:
  • the processor 802 is configured to assign all orders included in the corresponding order group to the same deliveryman in the order-waiting state for delivery when no new order to be delivered is obtained.
  • bus system 804 is used to implement connection communication between these components.
  • bus system 804 also includes a power bus, a control bus, and a status signal bus.
  • the various buses are labeled as bus system 804 in FIG. 8 .
  • the memory 803 in this embodiment of the present application is used to store various types of data to support the operation of the electronic device 800 .
  • Examples of such data include: any computer program used to operate on electronic device 800 .
  • the methods disclosed in the above embodiments of the present application may be applied to the processor 802 or implemented by the processor 802 .
  • the processor 802 may be an integrated circuit chip with signal processing capability. In the implementation process, each step of the above-mentioned method can be completed by an integrated logic circuit of hardware in the processor 802 or an instruction in the form of software.
  • the above-mentioned processor 802 may be a general-purpose processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like.
  • the processor 802 may implement or execute the methods, steps, and logical block diagrams disclosed in the embodiments of this application.
  • a general purpose processor may be a microprocessor or any conventional processor or the like.
  • the steps of the method disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor.
  • the software module may be located in a storage medium, and the storage medium is located in the memory 803, and the processor 802 reads the information in the memory 803, and completes the steps of the foregoing method in combination with its hardware.
  • the electronic device 800 may be implemented by one or more of Application Specific Integrated Circuit (ASIC), DSP, Programmable Logic Device (PLD), Complex Programmable Logic Device (CPLD) , Complex Programmable Logic Device), Field Programmable Gate Array (FPGA, Field-Programmable Gate Array), general-purpose processor, controller, microcontroller (MCU, Micro Controller Unit), microprocessor (Microprocessor), or other electronic Element implementation for performing the aforementioned method.
  • ASIC Application Specific Integrated Circuit
  • DSP Programmable Logic Device
  • CPLD Complex Programmable Logic Device
  • FPGA Field Programmable Gate Array
  • FPGA Field-Programmable Gate Array
  • general-purpose processor controller
  • MCU microcontroller
  • MCU Micro Controller Unit
  • Microprocessor Microprocessor
  • the memory 803 in this embodiment of the present application may be a volatile memory or a non-volatile memory, and may also include both volatile and non-volatile memory.
  • the non-volatile memory can be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), an erasable programmable read-only memory (EPROM, Erasable Programmable Read-only memory) Only Memory), Electrically Erasable Programmable Read-Only Memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), Magnetic Random Access Memory (FRAM, ferromagnetic random access memory), Flash Memory (Flash Memory), Magnetic Surface Memory , CD-ROM, or CD-ROM (Compact Disc Read-Only Memory); magnetic surface memory can be disk memory or tape memory.
  • RAM Random Access Memory
  • SRAM Static Random Access Memory
  • SSRAM Synchronous Static Random Access Memory
  • DRAM Dynamic Random Access Memory
  • SDRAM Synchronous Dynamic Random Access Memory
  • DDRSDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • ESDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • ESDRAM Enhanced Type Synchronous Dynamic Random Access Memory
  • SLDRAM Synchronous Link Dynamic Random Access Memory
  • DRRAM Direct Rambus Random Access Memory
  • DRRAM Direct Rambus Random Access Memory
  • an embodiment of the present application further provides a storage medium, that is, a computer storage medium, specifically a computer-readable storage medium, for example, including a memory 803 for storing a computer program, and the above-mentioned computer program can be processed by the electronic device 800
  • the device 802 is executed to complete the steps of the aforementioned method.
  • the computer-readable storage medium may be memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disk, or CD-ROM.

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Abstract

本申请公开了一种调度方法、装置、电子设备及存储介质。其中，方法包括：获取多个待配送订单；确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；从所述多种分组方式中确定最优分组方式；所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；基于所述最优分组方式，对所述多个待配送订单进行分组配送。

Description

调度方法、装置、电子设备及存储介质
相关申请的交叉引用
本申请基于申请号为202110336593.9、申请日为2021年03月29日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本申请涉及仓储物流技术领域，尤其涉及一种调度方法、装置、电子设备及存储介质。
背景技术
在物流配送场景中，为了提高配送订单的效率，配送员通常会根据自身经验匹配多个顺路的订单一起配送。然而，由于配送员的经验有限，匹配出的订单存在不顺路的情况，无法有效地提高配送订单的效率。
发明内容
为解决相关技术问题，本申请实施例提供一种调度方法、装置、电子设备及存储介质。
本申请实施例的技术方案是这样实现的：
本申请实施例提供了一种调度方法，包括：
获取多个待配送订单；确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；
从所述多种分组方式中确定最优分组方式；所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；
基于所述最优分组方式，对所述多个待配送订单进行分组配送。
上述方案中，所述确定针对所述多个待配送订单的多种分组方式，包括：
基于第一阈值及所述多个待配送订单中每个待配送订单的约定到达时刻，确定针对所述多个待配送订单的多种分组方式；其中，基于每种分组方式对所述多个待配送订单进行分组配送时，每个订单到达目的地的时刻 不超过相应的约定到达时刻，且每种分组方式的每个订单组包含的订单个数小于或等于第一阈值。
上述方案中，所述从所述多种分组方式中确定最优分组方式，包括：
从所述多种分组方式中确定订单组的个数最少的至少两种分组方式；
将所述至少两种分组方式中配送时长最短的分组方式确定为最优分组方式。
上述方案中，所述方法还包括：
针对每种分组方式，利用路径优化策略，确定相应分组方式的每个订单组的最优配送路径；并基于确定的每个订单组的最优配送路径，确定相应分组方式的配送时长；
基于每种分组方式的配送时长，从所述多种分组方式中确定最优分组方式。
上述方案中，所述利用路径优化策略，确定相应分组方式的每个订单组的最优配送路径，包括：
针对相应分组方式的每个订单组，确定相应订单组的至少一种配送路径；并从所述至少一种配送路径中确定最优配送路径；其中，所述最优配送路径的配送时长在所述至少一种配送路径中最短。
上述方案中，所述方法还包括：
针对相应分组方式的每个订单组，利用第一信息、第二信息和第三信息，确定相应订单组的每种配送路径的配送时长；并基于每种配送路径的配送时长，从所述至少一种配送路径中确定最优配送路径；其中，所述第一信息包含相应订单组包含的每个订单的目的地坐标；所述第二信息包含针对配送突发情况设置的预留时长；所述第三信息包含订单配送速度。
上述方案中，所述方法还包括：
获取历史订单相关的历史配送数据；
利用获取的历史配送数据，确定所述第二信息和所述第三信息。
上述方案中，所述基于所述最优分组方式，对所述多个待配送订单进行分组配送，包括：
针对所述最优分组方式的每个订单组，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
上述方案中，所述方法还包括：
监测配送员的状态切换操作；基于监测到的配送员的状态切换操作，更新配送员的状态；所述配送员的状态至少包含未签到状态、待排队状态、待接单状态、配送状态和休息状态。
上述方案中，所述将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送，包括：
针对所述最优分组方式的每个订单组，确定相应订单组的配送时长；基于相应订单组的配送时长，确定相应订单组的开始配送时刻；判断当前 时刻是否到达所述开始配送时刻；在当前时刻到达所述开始配送时刻的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
上述方案中，所述方法还包括：
在当前时刻未到达所述开始配送时刻的情况下，获取至少一个新的待配送订单；
针对当前未分配给配送员的全部待配送订单，重新确定多种分组方式；从重新确定的多种分组方式中确定新的最优分组方式；并基于新的最优分组方式，对当前未分配给配送员的全部待配送订单进行分组配送。
上述方案中，所述将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送，包括：
在未获取到新的待配送订单的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
本申请实施例还提供了一种调度装置，包括：
获取单元，配置为获取多个待配送订单；
第一处理单元，配置为确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；
第二处理单元，配置为从所述多种分组方式中确定最优分组方式；所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；
第三处理单元，配置为基于所述最优分组方式，对所述多个待配送订单进行分组配送。
本申请实施例还提供了一种电子设备，包括：处理器和配置为存储能够在处理器上运行的计算机程序的存储器；
其中，所述处理器配置为运行所述计算机程序时，执行上述任一方法的步骤。
本申请实施例还提供了一种存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现上述任一方法的步骤。
本申请实施例提供的调度方法、装置、电子设备及存储介质，获取多个待配送订单；确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；从所述多种分组方式中确定最优分组方式；所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；基于所述最优分组方式，对所述多个待配送订单进行分组配送。本申请实施例的方案，从针对多个待配送订单的多种分组方式中确定订单组的个数最少且配送时长最短的最优分组方式，并基于最优分组方式对多个待配送订单进行分组配送；如此，能够实 现订单配送的自动调度，即自动地为配送员分配匹配好的顺路订单(即一个订单组包含的订单)，使得配送员能够在尽可能短的时间内配送尽可能多的订单，同时，无需配送员根据自身经验进行订单匹配，匹配出的订单也不会存在不顺路的情况，能够有效地提高配送订单的效率。
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图1为本申请实施例调度方法的流程示意图；
图2为本申请应用实施例一种快递员状态流转示意图；
图3为本申请应用实施例另一种快递员状态流转示意图；
图4为本申请应用实施例系统自动指派流程的示意图；
图5为本申请应用实施例订单从支付到配送完成的流程示意图；
图6为本申请应用实施例集合单配送时长示意图；
图7为本申请实施例调度装置的结构示意图；
图8为本申请实施例电子设备的结构示意图。
具体实施方式
下面结合附图及实施例对本申请再作进一步详细的描述。
针对物流配送场景(比如线下零售商超门店进行订单配送)，配送员(也可以称为快递员或骑手)在接单取货时，可能会存在以下问题：
第一，为了提高配送订单的效率，配送员通常只能完全靠自身经验匹配顺路的订单，而对于新入职或对路况不熟悉的配送员，很难将顺路的订单进行匹配，匹配出的订单存在不顺路的情况，且无法准确判断送货的先后顺序。因此，对配送员的培训成本较大，订单的配送效率较低，从而使得用户体验较差。
第二，当订单量少时，配送员为了匹配更多的顺路订单，会在现场盲目等单，导致配送时间的浪费；或者，配送员会有挑单、抢单的现象(即抢重量轻、配送路程短的订单)，导致管理成本(比如门店管理成本)的浪费，使得管理成本较高。
第三，没有对配送员的配送环节进行系统自动化管理，也没有对配送员的状态进行监控和精细化管理，配送员通常自发地进行扫码接单，无法接收自动分配的任务，换句话说，订单的配送调度通过人工实现，管理成本较高。比如，线下零售商超门店有售后订单时，门店管理员需要根据配送员的位置及状态进行售后订单的人工指派。
基于此，在本申请的各种实施例中，从针对多个待配送订单的多种分组方式中确定订单组的个数最少且配送时长最短的最优分组方式，并基于最优分组方式对多个待配送订单进行分组配送；如此，能够实现订单配送的自动调度，即自动地为配送员分配匹配好的顺路订单(即一个订单组包 含的订单)，使得配送员能够在尽可能短的时间内配送尽可能多的订单，同时，无需配送员根据自身经验进行订单匹配，匹配出的订单也不会存在不顺路的情况，能够有效地提高配送订单的效率。订单的配送效率提高后，能够减少订单配送超时的情况，从而提升用户体验。
另外，在本申请的各种实施例中，通过对配送员的行程和状态进行监控，实现对配送员状态的精细化管理。
本申请实施例提供一种调度方法，应用于电子设备(比如服务器)，如图1所示，该方法包括：
步骤101：获取多个待配送订单；确定针对所述多个待配送订单的多种分组方式；
这里，每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；
步骤102：从所述多种分组方式中确定最优分组方式；
这里，所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；
步骤103：基于所述最优分组方式，对所述多个待配送订单进行分组配送。
在步骤101中，实际应用时，所述电子设备获取待配送订单的方式可以根据需求设置。比如，所述电子设备可以从本地订单池中获取待配送订单，而所述本地订单池中的订单可以是所述电子设备从其他电子设备(比如客户端)接收的订单；再比如，所述电子设备可以通过向其他电子设备(比如另一服务器)发送订单请求消息、并接收其他电子设备返回的订单消息的方式从其他电子设备获取待配送订单。
实际应用时，为了保证订单能够准时送达，一个订单组包含的订单个数不应该超过配送员的配送能力。
基于此，在一实施例中，所述确定针对所述多个待配送订单的多种分组方式，可以包括：
基于第一阈值及所述多个待配送订单中每个待配送订单的约定到达时刻，确定针对所述多个待配送订单的多种分组方式；
其中，基于每种分组方式对所述多个待配送订单进行分组配送时，每个订单到达目的地的时刻不超过相应的约定到达时刻，且每种分组方式的每个订单组包含的订单个数小于或等于第一阈值。
这里，确定的每种分组方式需要同时满足以下两个条件：
第一，基于相应分组方式对所述多个待配送订单进行分组配送时，每个订单到达目的地的时刻不超过相应的约定到达时刻(后续描述中可以记作第一条件)；
第二，相应分组方式的每个订单组包含的订单个数小于或等于第一阈值(后续描述中可以记作第二条件)。
因此，实际应用时，所述确定针对所述多个待配送订单的多种分组方式，可以理解为：基于第一阈值及所述多个待配送订单中每个待配送订单的约定到达时刻，确定满足第一条件和第二条件的多种分组方式。
实际应用时，在第一条件相关的判断过程中，即确定一种候选分组方式后，判断这种候选分组方式是否满足第一条件时，可以利用路径优化策略，确定该候选分组方式的每个订单组的最优配送路径，并基于确定的每个订单组的最优配送路径及当前时刻，利用第一信息、第二信息和第三信息，确定相应订单组包含的每个订单到达目的地的时刻是否超过相应的约定到达时刻。
其中，所述第一信息包含相应订单组包含的每个订单的目的地坐标；所述第二信息包含针对配送突发情况设置的预留时长(比如5分钟)；所述第三信息包含订单配送速度。另外，路径可以理解为订单的配送顺序，路径优化策略的基本思想是：在针对一个订单组的至少一种配送路径中，最优配送路径的配送时长最短。这里，也可以利用所述第一信息、所述第二信息和所述第三信息，确定每种配送路径的配送时长。
实际应用时，所述电子设备可以从本地或其他电子设备获取历史订单相关的历史配送数据，并利用获取的历史配送数据，确定所述第二信息和所述第三信息。所述历史配送数据可以包括历史订单的发起时刻、历史订单的约定到达时刻、历史订单的开始配送地坐标、历史订单的开始配送时刻、历史订单的目的地坐标、历史订单的到达时刻、呼叫用户的次数和时长、配送过程的停留时长(比如因信号灯停留或因步行配送、取货装车等原因停留)及历史订单的配送员等信息。
基于此，在一实施例中，所述方法还可以包括：
获取历史订单相关的历史配送数据；
利用获取的历史配送数据，确定所述第二信息和所述第三信息。
实际应用时，所述第二信息可以包括以下至少之一：
针对步行配送情况设置的预留时长(比如3分钟)；具体地，订单目的地可能楼层较高或未设置电梯，配送员需要爬楼梯进行配送，因此，为了保证订单能够准时送达，需要设置预留时长。
针对联系用户设置的预留时长(比如1分钟)；具体地，用户可能不方便接听电话，需要配送员多次呼叫，因此，为了保证订单能够准时送达，需要设置预留时长。
针对取货装车情况设置的预留时长(比如3分钟)；具体地，订单分配给配送员后，配送员需要领取相应货物，因此，为了保证订单能够准时送达，需要设置预留时长。
针对信号灯较多的情况设置的预留时长(比如3分钟)；具体地，信号灯数量大于第二阈值(可以根据需求设置)时，可以确定信号灯较多，为了保证订单能够准时送达，需要设置预留时长。
实际应用时，所述第一阈值可以根据配送员的配送能力设置，比如3。另外，也可以利用所述历史配送数据，确定配送员的配送能力。
在步骤102中，所述最优分组方式需要满足以下两个条件：
第一，所述最优分组方式的订单组的个数在所述多种分组方式中最少(后续描述中可以记作第三条件)；
第二，所述最优分组方式的配送时长在所述多种分组方式中最短(后续描述中可以记作第四条件)。
因此，实际应用时，所述从所述多种分组方式中确定最优分组方式，可以理解为：从所述多种分组方式中，确定满足第三条件和第四条件的最优分组方式。
实际应用时，对于每种分组方式，订单组的个数越少，每个订单组包含的订单个数越多。在每种分组方式已经满足第一条件和第二条件的情况下，即使一种分组方式的配送时长较长，基于该分组方式对所述多个待配送订单进行分组配送也不会导致订单超时。因此，为了使配送员一次能够配送尽可能多的订单，提高配送效率，所述第三条件的判断优先级可以高于所述第四条件的判断优先级。
具体地，所述第三条件的判断优先级高于所述第四条件的判断优先级，可以理解为：在所述多种分组方式中订单组的个数最少的分组方式与配送时长最短的分组方式不同的情况下，可以先判断所述多种分组方式中满足第三条件的分组方式，在仅有一种分组方式满足所述第三条件的情况下，将满足所述第三条件的分组方式确定为最优分组方式；在有至少两种分组方式满足所述第三条件的情况下，将满足所述第三条件的至少两种分组方式中满足所述第四条件的分组方式确定为最优分组方式，换句话说，将满足所述第三条件的至少两种分组方式中配送时长最短的分组方式确定为最优分组方式。
基于此，在一实施例中，所述从所述多种分组方式中确定最优分组方式，可以包括：
从所述多种分组方式中确定订单组的个数最少的至少两种分组方式；
将所述至少两种分组方式中配送时长最短的分组方式确定为最优分组方式。
实际应用时，在第四条件相关的判断过程中，需要确定每种分组方式的配送时长。
基于此，在一实施例中，所述方法还可以包括：
针对每种分组方式，利用所述路径优化策略，确定相应分组方式的每个订单组的最优配送路径；并基于确定的每个订单组的最优配送路径，确定相应分组方式的配送时长；
相应地，所述从所述多种分组方式中确定最优分组方式，可以包括：
基于每种分组方式的配送时长，从所述多种分组方式中确定最优分组 方式。
在一实施例中，基于所述路径优化策略的基本思想，所述利用所述路径优化策略，确定相应分组方式的每个订单组的最优配送路径，可以包括：
针对相应分组方式的每个订单组，确定相应订单组的至少一种配送路径；并从所述至少一种配送路径中确定最优配送路径；其中，所述最优配送路径的配送时长在所述至少一种配送路径中最短。
实际应用时，在确定最优配送路径的过程中，需要确定每种配送路径的配送时长。
基于此，在一实施例中，所述方法还可以包括：
针对相应分组方式的每个订单组，利用所述第一信息、所述第二信息和所述第三信息，确定相应订单组的每种配送路径的配送时长；
相应地，所述从所述至少一种配送路径中确定最优配送路径，可以包括：
基于每种配送路径的配送时长，从所述至少一种配送路径中确定最优配送路径。
对于步骤103，在一实施例中，所述基于所述最优分组方式，对所述多个待配送订单进行分组配送，可以包括：
针对所述最优分组方式的每个订单组，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
实际应用时，所述将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送，可以包括：所述电子设备将相应订单组包含的全部订单的相关信息发送给一个处于待接单状态的配送员所持有的终端。
实际应用时，为了减少对配送员的管理成本，可以对配送员的行程和状态进行监测，以实现对配送员的精细化管理。具体地，所述电子设备可以通过从配送员持有的终端实时获取配送员的位置来监测配送员的行程，并根据获取的位置确定配送员是否处于配送状态。或者，为了进一步对配送员的状态进行精细化管理，配送员也可以通过持有的终端执行状态切换操作，以切换自身的状态。
基于此，在一实施例中，所述方法还可以包括：
监测配送员的状态切换操作；基于监测到的配送员的状态切换操作，更新配送员的状态；所述配送员的状态至少包含未签到状态(也可以称为待签到状态)、待排队状态、待接单状态(也可以称为排队中状态)、配送状态(也可以称为配送中状态)和休息状态。
实际应用时，所述电子设备可以通过接收配送员持有的终端发送的消息来监测配送员的状态切换操作。
示例性地，配送员当天第一次登陆持有终端上的配送系统时，所述终端可以向所述电子设备发送登陆消息，所述电子设备接收到登陆消息后， 可以确定该配送员为未签到状态，并向所述终端发送未签到状态指示消息，以指示所述终端在所述配送系统中呈现未签到状态。
配送员可以点击所述配送系统中的签到按钮，触发所述终端向所述电子设备发送签到消息，所述电子设备接收到签到消息后，可以确定该配送员为待排队状态，并向所述终端发送待排队状态指示消息，以指示所述终端在所述配送系统中呈现待排队状态。或者，配送员在完成一个订单组的配送后，可以点击所述配送系统中的配送完成按钮，触发所述终端向所述电子设备发送配送完成消息，所述电子设备接收到配送完成消息后，可以确定该配送员为待排队状态，并向所述终端发送待排队状态指示消息，以指示所述终端在所述配送系统中呈现待排队状态。
配送员在确定自身能够进行订单配送的情况下，可以点击所述配送系统中的排队按钮，触发所述终端向所述电子设备发送排队消息，所述电子设备接收到排队消息后，可以确定该配送员为待接单状态，并向所述终端发送待接单状态指示消息，以指示所述终端在所述配送系统中呈现待接单状态。
所述终端接收并在所述配送系统中呈现所述电子设备发送的一个订单组包含的全部订单的相关信息后，配送员可以点击所述配送系统中的接单按钮，触发所述终端向所述电子设备发送接单消息，所述电子设备接收到接单消息后，可以确定该配送员为配送状态，并向所述终端发送配送状态指示消息，以指示所述终端在所述配送系统中呈现配送状态。
配送员可以在需要休息时点击所述配送系统中的休息按钮，触发所述终端向所述电子设备发送休息消息，所述电子设备接收到休息消息后，可以确定该配送员为休息状态，并向所述终端发送休息状态指示消息，以指示所述终端在所述配送系统中呈现休息状态。
实际应用时，所述配送员的状态还可以包括已签退状态，配送员可以在下班时点击所述配送系统中的签退按钮，触发所述终端向所述电子设备发送签退消息，所述电子设备接收到签退消息后，可以确定该配送员为已签退状态，并向所述终端发送已签退状态指示消息，以指示所述终端在所述配送系统中呈现已签退状态。
实际应用时，未分组的待配送订单可能会不断地增加，如果仅在积累一定数量的订单后再进行分组配送可能会导致一些订单超时，因此，在进行分组配送时，可以先确定在订单不超时的前提下，所述最优分组方式的每个订单组的开始配送时刻，并在当前时刻到达相应订单组的开始配送时刻的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
基于此，在一实施例中，所述将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送，可以包括：
针对所述最优分组方式的每个订单组，确定相应订单组的配送时长； 基于相应订单组的配送时长，确定相应订单组的开始配送时刻；判断当前时刻是否到达所述开始配送时刻；在当前时刻到达所述开始配送时刻的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
这里，确定相应订单组的配送时长时，可以先利用所述路径优化策略，确定相应订单组的最优配送路径，并利用所述第一信息、所述第二信息和所述第三信息确定所述最优配送路径的配送时长(即相应订单组的配送时长)。
相应地，在另一实施例中，所述方法还可以包括：
在当前时刻未到达所述开始配送时刻的情况下，获取至少一个新的待配送订单；
针对当前未分配给配送员的全部待配送订单，重新确定多种分组方式；从重新确定的多种分组方式中确定新的最优分组方式；并基于新的最优分组方式，对当前未分配给配送员的全部待配送订单进行分组配送。
实际应用时，当前未分配给配送员的全部待配送订单是动态变化的，所述全部待配送订单包含获取的至少一个新的待配送订单，以及在上次分组配送过程中未到达开始配送时刻的订单组包含的订单。
实际应用时，在当前时刻未到达所述开始配送时刻的情况下，如果一直未获取到新的待配送订单，所述电子设备可以在到达所述开始配送时刻时将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
基于此，在一实施例中，所述将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送，可以包括：
在未获取到新的待配送订单的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
本申请实施例提供的调度方法，获取多个待配送订单；确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；从所述多种分组方式中确定最优分组方式；所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；基于所述最优分组方式，对所述多个待配送订单进行分组配送。本申请实施例的方案，从针对多个待配送订单的多种分组方式中确定订单组的个数最少且配送时长最短的最优分组方式，并基于最优分组方式对多个待配送订单进行分组配送；如此，能够实现订单配送的自动调度，即自动地为配送员分配匹配好的顺路订单(即一个订单组包含的订单)，使得配送员能够在尽可能短的时间内配送尽可能多的订单，同时，无需配送员根据自身经验进行订单匹配，匹配出的订单也不会存在不顺路的情况，能够有效地提高配送订单的效率。订单的配送效率提高后，能够减少订单配送 超时的情况，从而提升用户体验。
另外，在本申请的各种实施例中，通过对配送员的行程和状态进行监控，实现了对配送员状态的精细化管理。
下面结合应用实施例对本申请再作进一步详细的描述。
在本应用实施例中，订单组称为集合单，包含单次分配给配送员的所有订单；集合单包含的订单个数称为集单数，即单次分配给配送员的所有订单的数量；第一阈值称为集单上限，是根据配送员能力确定的；最优分组方式的全部订单组称为最优集单组合；配送员称为快递员。
在本应用实施例中，对快递员的行程实行监控，并对快递员状态进行精细化管理。同时，以最晚配送时间(即最晚配送时刻)为基础，计算出最优集单组合和路径规划，实现订单的自动指派功能，避免快递员自己凭经验匹配订单、盲目等单、挑单和抢单的现象。这里，最晚配送时刻是指将订单指派给快递员后，快递员以不迟到为前提的最晚出发时刻。
图2和图3示出了快递员状态流转过程，下面结合图2和图3描述本应用实施例对快递员状态进行管理的方案。
如图2和图3所示，快递员包括以下状态：
待签到状态；用户(即快递员)当天第一次从用户终端打开(即登陆)配送系统时，快递员为待签到状态；
待排队状态；快递员在配送系统中点击签到后或在订单配送完成(订单状态可以是妥投或拒收)后，切换为待排队状态；
排队中状态(即待接单状态)；快递员在配送系统中点击排队后切换为排队中状态；
配送中状态；快递员在接单后自动切换为配送中状态；
休息中状态；快递员在配送系统中点击小休时，切换为休息中状态；
已签退状态；快递员在配送系统中点击签退后，切换为已签退状态。
在本应用实施例中，通过以上六种快递员状态，实现对快递员的精细化管理。并且，在对快递员进行精细化管理的基础上，建立订单自动指派算法的模型，并基于建立的算法模型构建配送系统。
图4示出了配送系统自动指派订单的流程，下面结合图4描述所述配送系统的功能。
所述配送系统包括：
生产模块，配置为对订单对应的货物进行拣货和打包。这里，如图5所示，订单从支付到配送完成包括以下流程：订单生成、等待支付、已付款、拣货中、拣货完成、开始打包、打包完成、揽件及配送完成(包括妥投和拒收)；拣货池包括拣货中的所有订单，打包池包括打包中的所用订单。
算法模块，配置为计算最优集单组合。具体地，所述算法模块包括数据解析模块和计算模块；所述数据解析模块配置为对基础数据进行解析，所述基础数据可以包括待配送订单的相关数据和历史订单的相关数据(即 上述历史订单相关的历史配送数据)。所述计算模块配置为计算集单组合的最晚配送时刻，并计算最优集单组合。
配送模块，配置为接收算法模块给出的最优集单组合，指派所述最优集单组合的每个集合单给排队中状态的快递员。快递员通过持有的终端接收到指派的集合单后，可以通过所述终端在门店进行扫码接单，在集合单的所有子单(即集合单包含的订单)都完成接单的情况下，快递员可以开始配送，在所有子单都配送完成(可以包括妥投或拒收)后，快递员可以切换回待排队状态，并通过在所述终端点击排队，切换为排队中状态，继续接收配送系统指派的集合单。在部分子单没有完成接单(即未揽件)的情况下，门店站长可以协助配送系统拉回快递员完成接单。
下面对所述数据解析模块和所述计算模块的功能进行详细说明。
首先，当订单进入拣货池时，所述数据解析模块开始对基础数据进行解析。
具体地，实际应用时，所述数据解析模块对基础数据进行解析的过程可以理解为数据预处理，在数据量较大时，可以提高计算模块的计算速度，缩短计算时长。数据预处理可以包括以下步骤：
步骤1：针对每个订单的配送地址(即目的地)进行坐标的转换，即将文本地址转换为经纬度坐标，并记录(即存储)转换后的坐标。
步骤2：根据历史订单的相关数据(即上述历史订单相关的历史配送数据)中快递员的定位信息(比如快递员到达小区门口的时刻以及快递员到达配送目的地的时刻)，计算每个订单的爬楼及打电话的时长(后续描述中记作单点服务时长)。
步骤3：根据历史订单的相关数据中快递员的定位信息(比如快递员到达门店的时刻以及快递员离开门店的时刻)，计算快递员每次配送需要的取货和装车时长(后续描述中记作缓冲(BUFFER)时长)。
这里，需要说明的是，上述针对配送突发情况设置的预留时长(即上述第二信息)包括所述单点服务时长和所述BUFFER时长。
步骤4：根据历史订单的相关数据中快递员的定位信息(比如快递员离开门店的时刻以及快递员到达配送目的地的时刻)，计算每个配送路区的骑行速度，即上述订单配送速度(第三信息)。这里，配送路区可以根据需求划分。
步骤5：针对拣货池中的所有订单，每两个订单之间进行充分的组合，换句话说，将拣货池中的所有订单中任意两个订单确定为一个集合单，得到多个集合单，并根据每个集合单中每个订单的目的地坐标，调用预设的地图模块确定每个集合单的导航距离，计算快递员骑行时长，并记录(即存储)在算法模型内。
其次，当订单进入打包池时，所述计算模块计算最优集单组合。
具体地，所述计算模块计算最优集单组合时，需要遵循集单规则和最 优选择规则。
所述集单规则的基本思想(即集单逻辑)是：当订单进入打包池时，在打包池中每个订单都能够完全履约(即上述第一条件，订单在约定到达时刻之前配送完成)、且集单数小于或等于集单上限(即上述第二条件)的前提下，以最晚离店配送时刻为集单时间的截至时刻进行订单集单(即实时地确定打包池中所有订单的多种分组方式)。
这里，一个集合单的最晚离店配送时刻可以等于用户的期望送达时刻(即上述约定到达时刻)—到达订单目的地所需的总路程时长—单点服务时长—BUFFER时长。
示例性地，如图6所示，假设一个集合单包含订单A、订单B和订单C，按照订单A—订单B—订单C的路径进行配送时到达订单目的地所需的总路程时长最短，为40分钟，订单C的期望送达时刻为9：00，单点服务时长和BUFFER时长均为3分钟；此时，可以确定该集合单的最晚离店配送时刻为8：08(9：00—40分钟—9分钟(3×3分钟)—3分钟)。
示例性地，假设当前打包池没有订单，而有三个订单(分别为订单D、订单E和订单F)将要依次进入打包池，集单上限为3，当前时刻为9：00。订单D进入打包池时，所述计算模块会先计算订单D离店配送的最晚配送时刻(假设为9：10)，此时，订单D还可以再等待匹配10分钟，在等待10分钟后没有新的订单进入打包池，或者进入打包池的新的订单无法与订单D匹配(即由于新的订单和/或订单D会超时配送，所以两个订单无法组成集合单)的情况下，配送系统可以将订单D直接指派给快递员进行配送(即所述计算模块可以直接将订单D作为最优集单组合发送给配送模块)。在10分钟内订单E进入打包池，且订单E能够与订单D匹配(即订单E和订单D能够在配送不超时的前提下组成集合单)的情况下，所述计算模块会计算订单D和订单E的最优配送路径，即计算先配送订单D后配送订单E所需的配送时长以及先配送订单E后配送订单D所需的配送时长，比较哪种路径的配送时长最短；假设计算模块计算出先配送订单D后配送订单E所需的配送时长最短，该最优配送路径对应的最晚离店配送时刻为9：08，且当前时刻为9：05，那么此时订单D和订单E可以再等待匹配3分钟。在等待3分钟后没有新的订单进入打包池，或者进入打包池的新的订单无法与订单D和/或订单E匹配的情况下，配送系统可以将订单D和订单E作为最优集单组合包含的一个集合单指派给一个快递员进行配送。在3分钟内订单F进入打包池，且订单F能够与订单D和订单E匹配的情况下，所述计算模块会计算订单D、订单E和订单F之间的最优配送路径，即在“订单D—订单E—订单F”、“订单D—订单F—订单E”、“订单E—订单D—订单F”、“订单E—订单F—订单D”、“订单F—订单D—订单E”和“订单F—订单E—订单D”六种配送路径中确定配送时长最短的最优配送路径，并计算出最优配送路径对应的最晚离店配送时刻，在还有等待时间(即当 前时刻未到达最晚离店配送时刻)的情况下，继续等待新的订单进入打包池并进行订单匹配；在没有等待时间(即当前时刻到达最晚离店配送时刻)的情况下，配送系统可以将订单D、订单E和订单F作为最优集单组合包含的一个集合单指派给一个快递员进行配送。
所述最优选择规则的基本思想是：对于按照所述集单规则的基本思想确定的多种订单分组方式(每个订单都能够履约、且每个集合单的集单数小于或等于集单上限)，根据订单分组方式的集合单个数，对多种订单分组方式从小到大进行排序(集合单个数越小代表集单数越大，即快递员一次配送的订单越多)；并根据订单分组方式所需的配送时长，对多种订单分组方式从小到大进行排序；根据两种订单分组方式的排序结果，确定最优分组方式，即得到最优集单组合。这里，确定最优集单组合时，以集合单个数最小的订单分组方式(即上述第三条件)为第一优先级、并以配送时长最短的订单分组方式(即上述第四条件)为第二优先级，在集合单个数最小的订单分组方式与配送时长最短的订单分组方式不同的情况下，将集合单个数最小的订单分组方式确定为最优分组方式；在集合单个数最小的订单分组方式与配送时长最短的订单分组方式相同的情况下，将同时满足这两个条件的订单分组方式确定为最优分组方式，得到最优集单组合，并将最优集单组合中到达最晚离店配送时刻的集合单指派给排队中状态的快递员。
示例性地，假设当前打包池有五个订单(分别为订单G、订单H、订单I、订单J和订单K)，集单上限为3，在保证订单全部履约的情况下，可计算出三种组合(即上述分组方式)，分别为：
组合一：集合单1(订单G、订单H和订单I)和集合单2(订单J和订单K)；
组合二：集合单3(订单G和订单H)和集合单4(订单I、订单J和订单K)；
组合三：集合单5(订单G和订单H)、集合单6(订单I)和集合单7(订单J和订单K)；
并假设组合一所需的配送时长为50分钟、组合二所需的配送时长为40分钟且组合三所需的配送时长为35分钟；此时，由于组合二满足了集合单个数最小以及配送时长最短的条件，可以确定组合二为最优分组方式，即确定集合单3和集合单4为最优集单组合。
实际应用时，由于集合单4的集单数已经到达集单上限，因此，可以直接将集合单4(订单I、订单J和订单K)指派给排队中的快递员。当然，也可以判断集合单4是否到达最晚离店配送时刻，在到达最晚离店配送时刻的情况下将集合单4指派给排队中的快递员。
本应用实施例提供的方案，对快递员的配送状态进行精细化的监控，构建了订单自动指派的算法逻辑，并对集合单进行了路径规划；如此，能 够有效地提高配送订单的效率，提升用户体验。
为了实现本申请实施例的方法，本申请实施例还提供了一种调度装置，如图7所示，该装置包括：
获取单元701，配置为获取多个待配送订单；
第一处理单元702，配置为确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；
第二处理单元703，配置为从所述多种分组方式中确定最优分组方式；所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；
第三处理单元704，配置为基于所述最优分组方式，对所述多个待配送订单进行分组配送。
其中，在一实施例中，所述第一处理单元702，配置为基于第一阈值及所述多个待配送订单中每个待配送订单的约定到达时刻，确定针对所述多个待配送订单的多种分组方式；其中，基于每种分组方式对所述多个待配送订单进行分组配送时，每个订单到达目的地的时刻不超过相应的约定到达时刻，且每种分组方式的每个订单组包含的订单个数小于或等于第一阈值。
在一实施例中，所述第二处理单元703，配置为：
从所述多种分组方式中确定订单组的个数最少的至少两种分组方式；
将所述至少两种分组方式中配送时长最短的分组方式确定为最优分组方式。
在一实施例中，所述第二处理单元703，配置为：
针对每种分组方式，利用路径优化策略，确定相应分组方式的每个订单组的最优配送路径；并基于确定的每个订单组的最优配送路径，确定相应分组方式的配送时长；
基于每种分组方式的配送时长，从所述多种分组方式中确定最优分组方式。
在一实施例中，所述第二处理单元703，配置为针对相应分组方式的每个订单组，确定相应订单组的至少一种配送路径；并从所述至少一种配送路径中确定最优配送路径；其中，所述最优配送路径的配送时长在所述至少一种配送路径中最短。
在一实施例中，所述第二处理单元703，配置为针对相应分组方式的每个订单组，利用第一信息、第二信息和第三信息，确定相应订单组的每种配送路径的配送时长；并基于每种配送路径的配送时长，从所述至少一种配送路径中确定最优配送路径；其中，所述第一信息包含相应订单组包含的每个订单的目的地坐标；所述第二信息包含针对配送突发情况设置的预留时长；所述第三信息包含订单配送速度。
在一实施例中，所述获取单元701，配置为获取历史订单相关的历史配送数据；
所述第二处理单元703，配置为利用获取的历史配送数据，确定所述第二信息和所述第三信息。
在一实施例中，所述第三处理单元704，配置为针对所述最优分组方式的每个订单组，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
在一实施例中，该装置还包括监测单元，配置为监测配送员的状态切换操作；基于监测到的配送员的状态切换操作，更新配送员的状态；所述配送员的状态至少包含未签到状态、待排队状态、待接单状态、配送状态和休息状态。
在一实施例中，所述第三处理单元704，配置为针对所述最优分组方式的每个订单组，确定相应订单组的配送时长；基于相应订单组的配送时长，确定相应订单组的开始配送时刻；判断当前时刻是否到达所述开始配送时刻；在当前时刻到达所述开始配送时刻的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
在一实施例中，所述获取单元701，配置为在当前时刻未到达所述开始配送时刻的情况下，获取至少一个新的待配送订单；
所述第一处理单元702，配置为针对当前未分配给配送员的全部待配送订单，重新确定多种分组方式；
所述第二处理单元703，配置为从重新确定的多种分组方式中确定新的最优分组方式；
所述第三处理单元704，配置为基于新的最优分组方式，对当前未分配给配送员的全部待配送订单进行分组配送。
在一实施例中，所述第三处理单元704，配置为在所述获取单元701未获取到新的待配送订单的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
实际应用时，所述获取单元701和所述监测单元可由该装置中的处理器结合通信接口实现；所述第一处理单元702、所述第二处理单元703和所述第三处理单元704可由该装置中的处理器实现。
需要说明的是：上述实施例提供的调度装置在进行配送调度时，仅以上述各程序模块的划分进行举例说明，实际应用时，可以根据需要而将上述处理分配由不同的程序模块完成，即将装置的内部结构划分成不同的程序模块，以完成以上描述的全部或者部分处理。另外，上述实施例提供的调度装置与调度方法实施例属于同一构思，其具体实现过程详见方法实施例，这里不再赘述。
基于上述程序模块的硬件实现，且为了实现本申请实施例的方法，本申请实施例还提供了一种电子设备，如图8所示，该电子设备800包括：
通信接口801，能够与其他电子设备进行信息交互；
处理器802，与所述通信接口801连接，以实现与其他电子设备进行信息交互，配置为运行计算机程序时，执行上述一个或多个技术方案提供的方法；
存储器803，存储能够在所述处理器802上运行的计算机程序。
具体地，所述处理器802，配置为：
获取多个待配送订单；确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；
从所述多种分组方式中确定最优分组方式；所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；
基于所述最优分组方式，对所述多个待配送订单进行分组配送。
其中，在一实施例中，所述处理器802，配置为基于第一阈值及所述多个待配送订单中每个待配送订单的约定到达时刻，确定针对所述多个待配送订单的多种分组方式；其中，基于每种分组方式对所述多个待配送订单进行分组配送时，每个订单到达目的地的时刻不超过相应的约定到达时刻，且每种分组方式的每个订单组包含的订单个数小于或等于第一阈值。
在一实施例中，所述处理器802，配置为：
从所述多种分组方式中确定订单组的个数最少的至少两种分组方式；
将所述至少两种分组方式中配送时长最短的分组方式确定为最优分组方式。
在一实施例中，所述处理器802，配置为：
针对每种分组方式，利用路径优化策略，确定相应分组方式的每个订单组的最优配送路径；并基于确定的每个订单组的最优配送路径，确定相应分组方式的配送时长；
基于每种分组方式的配送时长，从所述多种分组方式中确定最优分组方式。
在一实施例中，所述处理器802，配置为针对相应分组方式的每个订单组，确定相应订单组的至少一种配送路径；并从所述至少一种配送路径中确定最优配送路径；其中，所述最优配送路径的配送时长在所述至少一种配送路径中最短。
在一实施例中，所述处理器802，配置为针对相应分组方式的每个订单组，利用第一信息、第二信息和第三信息，确定相应订单组的每种配送路径的配送时长；并基于每种配送路径的配送时长，从所述至少一种配送路径中确定最优配送路径；其中，所述第一信息包含相应订单组包含的每个订单的目的地坐标；所述第二信息包含针对配送突发情况设置的预留时长；所述第三信息包含订单配送速度。
在一实施例中，所述处理器802，配置为：
获取历史订单相关的历史配送数据；
利用获取的历史配送数据，确定所述第二信息和所述第三信息。
在一实施例中，所述处理器802，配置为针对所述最优分组方式的每个订单组，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
在一实施例中，所述处理器802，配置为监测配送员的状态切换操作；基于监测到的配送员的状态切换操作，更新配送员的状态；所述配送员的状态至少包含未签到状态、待排队状态、待接单状态、配送状态和休息状态。
在一实施例中，所述处理器802，配置为针对所述最优分组方式的每个订单组，确定相应订单组的配送时长；基于相应订单组的配送时长，确定相应订单组的开始配送时刻；判断当前时刻是否到达所述开始配送时刻；在当前时刻到达所述开始配送时刻的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
在一实施例中，所述处理器802，配置为：
在当前时刻未到达所述开始配送时刻的情况下，获取至少一个新的待配送订单；
针对当前未分配给配送员的全部待配送订单，重新确定多种分组方式；从重新确定的多种分组方式中确定新的最优分组方式；并基于新的最优分组方式，对当前未分配给配送员的全部待配送订单进行分组配送。
在一实施例中，所述处理器802，配置为在未获取到新的待配送订单的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
需要说明的是：所述处理器802具体执行上述操作的过程详见方法实施例，这里不再赘述。
当然，实际应用时，电子设备800中的各个组件通过总线系统804耦合在一起。可理解，总线系统804用于实现这些组件之间的连接通信。总线系统804除包括数据总线之外，还包括电源总线、控制总线和状态信号总线。但是为了清楚说明起见，在图8中将各种总线都标为总线系统804。
本申请实施例中的存储器803用于存储各种类型的数据以支持电子设备800的操作。这些数据的示例包括：用于在电子设备800上操作的任何计算机程序。
上述本申请实施例揭示的方法可以应用于处理器802中，或者由处理器802实现。处理器802可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述方法的各步骤可以通过处理器802中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器802可以是通用处理器、数字信号处理器(DSP，Digital Signal Processor)，或者其他可编程逻辑器 件、分立门或者晶体管逻辑器件、分立硬件组件等。处理器802可以实现或者执行本申请实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者任何常规的处理器等。结合本申请实施例所公开的方法的步骤，可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于存储介质中，该存储介质位于存储器803，处理器802读取存储器803中的信息，结合其硬件完成前述方法的步骤。
在示例性实施例中，电子设备800可以被一个或多个应用专用集成电路(ASIC，Application Specific Integrated Circuit)、DSP、可编程逻辑器件(PLD，Programmable Logic Device)、复杂可编程逻辑器件(CPLD，Complex Programmable Logic Device)、现场可编程门阵列(FPGA，Field-Programmable Gate Array)、通用处理器、控制器、微控制器(MCU，Micro Controller Unit)、微处理器(Microprocessor)、或者其他电子元件实现，用于执行前述方法。
可以理解，本申请实施例的存储器803可以是易失性存储器或者非易失性存储器，也可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(ROM，Read Only Memory)、可编程只读存储器(PROM，Programmable Read-Only Memory)、可擦除可编程只读存储器(EPROM，Erasable Programmable Read-Only Memory)、电可擦除可编程只读存储器(EEPROM，Electrically Erasable Programmable Read-Only Memory)、磁性随机存取存储器(FRAM，ferromagnetic random access memory)、快闪存储器(Flash Memory)、磁表面存储器、光盘、或只读光盘(CD-ROM，Compact Disc Read-Only Memory)；磁表面存储器可以是磁盘存储器或磁带存储器。易失性存储器可以是随机存取存储器(RAM，Random Access Memory)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(SRAM，Static Random Access Memory)、同步静态随机存取存储器(SSRAM，Synchronous Static Random Access Memory)、动态随机存取存储器(DRAM，Dynamic Random Access Memory)、同步动态随机存取存储器(SDRAM，Synchronous Dynamic Random Access Memory)、双倍数据速率同步动态随机存取存储器(DDRSDRAM，Double Data Rate Synchronous Dynamic Random Access Memory)、增强型同步动态随机存取存储器(ESDRAM，Enhanced Synchronous Dynamic Random Access Memory)、同步连接动态随机存取存储器(SLDRAM，SyncLink Dynamic Random Access Memory)、直接内存总线随机存取存储器(DRRAM，Direct Rambus Random Access Memory)。本申请实施例描述的存储器旨在包括但不限于这些和任意其他适合类型的存储器。
在示例性实施例中，本申请实施例还提供了一种存储介质，即计算机存储介质，具体为计算机可读存储介质，例如包括存储计算机程序的存储 器803，上述计算机程序可由电子设备800的处理器802执行，以完成前述方法所述步骤。计算机可读存储介质可以是FRAM、ROM、PROM、EPROM、EEPROM、Flash Memory、磁表面存储器、光盘、或CD-ROM等存储器。
需要说明的是：“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。
另外，本申请实施例所记载的技术方案之间，在不冲突的情况下，可以任意组合。
以上所述，仅为本申请的较佳实施例而已，并非用于限定本申请的保护范围。

Claims (15)

  1. 一种调度方法，包括：
    获取多个待配送订单；确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；
    从所述多种分组方式中确定最优分组方式；所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；
    基于所述最优分组方式，对所述多个待配送订单进行分组配送。
  2. 根据权利要求1所述的方法，其中，所述确定针对所述多个待配送订单的多种分组方式，包括：
    基于第一阈值及所述多个待配送订单中每个待配送订单的约定到达时刻，确定针对所述多个待配送订单的多种分组方式；其中，基于每种分组方式对所述多个待配送订单进行分组配送时，每个订单到达目的地的时刻不超过相应的约定到达时刻，且每种分组方式的每个订单组包含的订单个数小于或等于第一阈值。
  3. 根据权利要求1所述的方法，其中，所述从所述多种分组方式中确定最优分组方式，包括：
    从所述多种分组方式中确定订单组的个数最少的至少两种分组方式；
    将所述至少两种分组方式中配送时长最短的分组方式确定为最优分组方式。
  4. 根据权利要求1所述的方法，其中，所述方法还包括：
    针对每种分组方式，利用路径优化策略，确定相应分组方式的每个订单组的最优配送路径；并基于确定的每个订单组的最优配送路径，确定相应分组方式的配送时长；
    基于每种分组方式的配送时长，从所述多种分组方式中确定最优分组方式。
  5. 根据权利要求4所述的方法，其中，所述利用路径优化策略，确定相应分组方式的每个订单组的最优配送路径，包括：
    针对相应分组方式的每个订单组，确定相应订单组的至少一种配送路径；并从所述至少一种配送路径中确定最优配送路径；其中，所述最优配送路径的配送时长在所述至少一种配送路径中最短。
  6. 根据权利要求5所述的方法，其中，所述方法还包括：
    针对相应分组方式的每个订单组，利用第一信息、第二信息和第三信息，确定相应订单组的每种配送路径的配送时长；并基于每种配送路 径的配送时长，从所述至少一种配送路径中确定最优配送路径；其中，所述第一信息包含相应订单组包含的每个订单的目的地坐标；所述第二信息包含针对配送突发情况设置的预留时长；所述第三信息包含订单配送速度。
  7. 根据权利要求6所述的方法，其中，所述方法还包括：
    获取历史订单相关的历史配送数据；
    利用获取的历史配送数据，确定所述第二信息和所述第三信息。
  8. 根据权利要求1至7任一项所述的方法，其中，所述基于所述最优分组方式，对所述多个待配送订单进行分组配送，包括：
    针对所述最优分组方式的每个订单组，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
  9. 根据权利要求8所述的方法，其中，所述方法还包括：
    监测配送员的状态切换操作；基于监测到的配送员的状态切换操作，更新配送员的状态；所述配送员的状态至少包含未签到状态、待排队状态、待接单状态、配送状态和休息状态。
  10. 根据权利要求8所述的方法，其中，所述将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送，包括：
    针对所述最优分组方式的每个订单组，确定相应订单组的配送时长；基于相应订单组的配送时长，确定相应订单组的开始配送时刻；判断当前时刻是否到达所述开始配送时刻；在当前时刻到达所述开始配送时刻的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
  11. 根据权利要求10所述的方法，其中，所述方法还包括：
    在当前时刻未到达所述开始配送时刻的情况下，获取至少一个新的待配送订单；
    针对当前未分配给配送员的全部待配送订单，重新确定多种分组方式；从重新确定的多种分组方式中确定新的最优分组方式；并基于新的最优分组方式，对当前未分配给配送员的全部待配送订单进行分组配送。
  12. 根据权利要求11所述的方法，其中，所述将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送，包括：
    在未获取到新的待配送订单的情况下，将相应订单组包含的全部订单分配给同一个处于待接单状态的配送员进行配送。
  13. 一种调度装置，包括：
    获取单元，配置为获取多个待配送订单；
    第一处理单元，配置为确定针对所述多个待配送订单的多种分组方式；每种分组方式用于将所述多个待配送订单划分为至少一个订单组；每个订单组包含至少一个订单；
    第二处理单元，配置为从所述多种分组方式中确定最优分组方式； 所述最优分组方式的订单组的个数在所述多种分组方式中最少，且所述最优分组方式的配送时长在所述多种分组方式中最短；
    第三处理单元，配置为基于所述最优分组方式，对所述多个待配送订单进行分组配送。
  14. 一种电子设备，包括：处理器和配置为存储能够在处理器上运行的计算机程序的存储器；
    其中，所述处理器配置为运行所述计算机程序时，执行权利要求1至12任一项所述方法的步骤。
  15. 一种存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现权利要求1至12任一项所述方法的步骤。
PCT/CN2022/079956 2021-03-29 2022-03-09 调度方法、装置、电子设备及存储介质 WO2022206323A1 (zh)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117094536A (zh) * 2023-10-19 2023-11-21 青岛冠成软件有限公司 一种订单数据分析方法及系统
CN117910915A (zh) * 2024-01-08 2024-04-19 嘉兴众膳餐饮管理有限公司 一种配餐调度方法及智能送餐溯源系统

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113095553A (zh) * 2021-03-29 2021-07-09 北京沃东天骏信息技术有限公司 调度方法、装置、电子设备及存储介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105719010A (zh) * 2015-07-24 2016-06-29 北京小度信息科技有限公司 配送任务的处理方法及装置
CN107392412A (zh) * 2017-06-05 2017-11-24 北京小度信息科技有限公司 订单调度方法和装置
CN107748923A (zh) * 2016-08-29 2018-03-02 北京三快在线科技有限公司 订单处理方法、装置及服务器
WO2018074851A1 (ko) * 2016-10-18 2018-04-26 주식회사 우아한형제들 배달주문 분배시스템 및 방법
CN111582612A (zh) * 2019-02-15 2020-08-25 拉扎斯网络科技（上海）有限公司 订单分配方法、装置、电子设备及计算机可读存储介质
CN113095553A (zh) * 2021-03-29 2021-07-09 北京沃东天骏信息技术有限公司 调度方法、装置、电子设备及存储介质

Family Cites Families (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107392513B (zh) * 2017-01-26 2018-12-28 北京小度信息科技有限公司 订单处理方法和装置
CN107180276B (zh) * 2017-05-23 2020-06-30 大连海事大学 一种o2o外卖平台智能调度与路线优化方法
CN107292701A (zh) * 2017-05-25 2017-10-24 北京小度信息科技有限公司 订单分组方法和装置
CN107292709A (zh) * 2017-06-14 2017-10-24 北京小度信息科技有限公司 订单处理方法及装置
CN109118310B (zh) * 2017-06-23 2022-03-01 北京星选科技有限公司 订单处理方法和装置
CN108074031B (zh) * 2017-06-29 2021-02-02 北京小度信息科技有限公司 订单组分配方法及装置
CN107844933A (zh) * 2017-09-21 2018-03-27 北京小度信息科技有限公司 订单处理方法及装置
CN109816132A (zh) * 2017-11-20 2019-05-28 北京京东尚科信息技术有限公司 信息生成方法和装置
CN110070312B (zh) * 2018-01-24 2023-12-08 北京京东乾石科技有限公司 订单处理方法和装置
CN110443397B (zh) * 2018-05-04 2022-12-09 日日顺供应链科技股份有限公司 一种订单配送方法
CN108665179A (zh) * 2018-05-17 2018-10-16 北京顺丰同城科技有限公司 物流调度方法、装置、电子设备以及计算机可读存储介质
CN109214551B (zh) * 2018-08-08 2022-08-26 北京三快在线科技有限公司 一种配送调度方法及装置
CN110969274A (zh) * 2018-09-28 2020-04-07 北京三快在线科技有限公司 一种预测配送时间的方法、装置及计算机可读存储介质
CN109359912B (zh) * 2018-10-10 2022-03-25 餐道信息科技有限公司 一种智能并单及派单方法
CN109242214A (zh) * 2018-10-25 2019-01-18 中国联合网络通信集团有限公司 配送路线规划方法和配送路线规划装置
CN111429049A (zh) * 2019-01-10 2020-07-17 北京京东尚科信息技术有限公司 物品订单的配送方法、系统、电子设备及可读存储介质
CN113095531A (zh) * 2019-08-20 2021-07-09 南京领行科技股份有限公司 一种派单方法和装置

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105719010A (zh) * 2015-07-24 2016-06-29 北京小度信息科技有限公司 配送任务的处理方法及装置
CN107748923A (zh) * 2016-08-29 2018-03-02 北京三快在线科技有限公司 订单处理方法、装置及服务器
WO2018074851A1 (ko) * 2016-10-18 2018-04-26 주식회사 우아한형제들 배달주문 분배시스템 및 방법
CN107392412A (zh) * 2017-06-05 2017-11-24 北京小度信息科技有限公司 订单调度方法和装置
CN111582612A (zh) * 2019-02-15 2020-08-25 拉扎斯网络科技（上海）有限公司 订单分配方法、装置、电子设备及计算机可读存储介质
CN113095553A (zh) * 2021-03-29 2021-07-09 北京沃东天骏信息技术有限公司 调度方法、装置、电子设备及存储介质

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117094536A (zh) * 2023-10-19 2023-11-21 青岛冠成软件有限公司 一种订单数据分析方法及系统
CN117094536B (zh) * 2023-10-19 2024-01-12 青岛冠成软件有限公司 一种订单数据分析方法及系统
CN117910915A (zh) * 2024-01-08 2024-04-19 嘉兴众膳餐饮管理有限公司 一种配餐调度方法及智能送餐溯源系统

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