CN107437146B - Order supply and demand scheduling method, system, computer equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses an order supply and demand scheduling method, a system, computer equipment and a storage medium, wherein the order supply and demand scheduling method comprises the following steps: data mining is carried out on historical order data and preferential activity information, and potential order data are predicted; filtering the real-time order data to determine order data to be preempted; and dispatching delivery personnel according to the potential order data, the order data to be preempted and the information of the delivery personnel. According to the method and the device for dispatching the order, the potential order data and the order data to be preempted are obtained, and dispatching personnel are dispatched according to the potential order data, the order data to be preempted and the dispatching personnel information, so that the possibility of the occurrence of an order bottleneck can be prevented and reduced, the effect of predicting the outbreak of the order in advance and reasonably configuring the transport capacity is achieved, the rapid experience of order preemption is improved, and the order receiving quantity and the order flow rate of the dispatching personnel are increased.
Description
Technical Field
The embodiment of the invention relates to the technical field of internet, in particular to an order supply and demand scheduling method, an order supply and demand scheduling system, computer equipment and a storage medium.
Background
With the rapid development of economy and the popularization of the internet, especially the rise of electronic commerce, the traditional consumption mode of people is changed, the demands of people are increased day by day, and the development of the express industry is driven. The development of the express industry shortens the distance between people and brings great convenience to the life of people.
At present, most of typical order distribution scheduling systems collect real-time order data, and automatically re-distribute orders or manually communicate with distribution personnel through customer service according to orders which fail to distribute orders and are not subjected to order grabbing by people for a long time so as to achieve the functions of evacuating and relieving the pressure of the existing orders.
However, the above prior art can only solve the bottleneck problem of the order to be held, and cannot prevent and reduce the possibility of the bottleneck of the order.
Disclosure of Invention
The embodiment of the invention provides an order supply and demand scheduling method, an order supply and demand scheduling system, computer equipment and a storage medium, and aims to solve the problem that the prior art cannot prevent and reduce the occurrence of order bottlenecks.
In a first aspect, an embodiment of the present invention provides an order supply and demand scheduling method, where the method includes:
data mining is carried out on historical order data and preferential activity information, and potential order data are predicted;
filtering the real-time order data to determine order data to be preempted;
and dispatching delivery personnel according to the potential order data, the order data to be preempted and the information of the delivery personnel.
In a second aspect, an embodiment of the present invention further provides an order supply and demand scheduling system, where the system includes:
the potential order prediction module is used for carrying out data mining on historical order data and preferential activity information to predict potential order data;
the order acquisition module to be preempted is used for filtering the real-time order data and determining the order data to be preempted;
and the delivery personnel scheduling module is used for scheduling delivery personnel according to the potential order data, the order data to be robbed and the delivery personnel information.
In a third aspect, an embodiment of the present invention further provides a computer device, where the computer device includes:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the order supply and demand scheduling method as described above.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the order supply and demand scheduling method described above.
According to the method and the device, the potential order data and the order data to be preempted are obtained, and the dispatching personnel are dispatched according to the potential order data, the order data to be preempted and the dispatching personnel information, so that the possibility of the occurrence of an order bottleneck can be prevented and reduced, the outbreak of the order can be predicted in advance, the transport capacity can be configured reasonably, the rapid experience of order preemption is improved, and the order receiving quantity and the order flow rate of the dispatching personnel can be increased.
Drawings
FIG. 1 is a flowchart illustrating an order demand and supply scheduling method according to an embodiment of the present invention;
FIG. 2 is a flowchart of an order demand and supply scheduling method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an order supply and demand scheduling system in the third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an order demand and supply scheduling computer device in the fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of an order demand and supply dispatching method according to an embodiment of the present invention, which may be executed by an order demand and supply dispatching system, where the system may be implemented by software and/or hardware. As shown in fig. 1, the method includes:
and S110, carrying out data mining on the historical order data and the preferential activity information, and predicting potential order data.
In particular, the historical order data may include order data for different regions and different time periods that have been completed in the past, including, for example, order account, order location, order quantity, and order time. In this embodiment, which accounts are high-frequency users with higher order placing frequency can be analyzed through the order accounts; the specific position of order distribution can be analyzed through the order position; the order quantity of different accounts of each area which appears in different time periods can be analyzed by combining the order quantity, the order time, the order position and the order account. Generally, the offer may include full or reduced price activities at particular times, such as holidays, such as buy-one-gift, full-ten-one-minus, and commodity-reduced activities. The order which is likely to occur in the future can also be predicted according to the preferential activity information. Therefore, through data mining by combining historical order data and preferential activity information, the order which is likely to appear in the future, namely the potential order data, can be predicted.
It should be noted that, when potential orders that may appear in different time periods of each future delivery area are predicted according to historical order data and preferential activities, the predicted potential orders of each delivery area are only one type of orders that may appear in the future, and therefore, there is a possibility that the potential orders do not appear. When the potential order does not occur according to the predicted result, the order supply and demand scheduling system can record the order data actually occurring at the moment, and add the order data actually occurring to the historical order data so as to perform data mining based on the order data and update the next predicted result.
Preferably, the historical order data includes at least one of: order data of a hot spot area, order data of a large number of merchants and order data of high-frequency individual users.
In the embodiment, the historical orders can be understood as orders of historical hot spot areas with large order quantity, orders of historical large-block merchants and orders of historical high-frequency individual users; the order statistics method can also be understood as analyzing which hot spot areas where the historical orders occur, which large businesses where the historical orders occur and which individual users with higher ordering frequency are from massive historical data, and further performing statistics on the data corresponding to the hot spot areas, the large businesses and the high-frequency individual users. Generally, a large number of orders are issued in areas similar to hot spots, a large number of merchants and high-frequency individual users, especially the same rule and the same frequency are issued for the hot spots and the high-frequency individual users, so that a certain strategy can be formulated according to the ordering habits of the hot spots and the high-frequency individual users, for example, the order distribution conditions of each distribution area in different time periods can be obtained by performing statistical analysis according to the ordering rules of the hot spots and the high-frequency individual users in different areas and/or different time periods, and thus the allocation strategy can be determined according to the order distribution conditions.
And S120, filtering the real-time order data and determining the order data to be preempted.
Specifically, the real-time order data includes order data that has completed the order taking and order data that has not been taken, and the order supply and demand scheduling system needs to filter the acquired real-time order data, filter the order data that has completed the order taking, and retain the order data that has not been taken. Generally, each real-time order data may include an order placing account, an order placing position, an order placing time and an order placing quantity of the real-time order, and the real-time order data may be order data of online shopping, order data temporarily issued by a user, and the like. Similarly, each data of the order to be preempted also includes the order placing account, the order placing position, the order placing time and the order placing quantity of the order to be preempted.
And S130, dispatching delivery personnel according to the potential order data, the order data to be preempted and the delivery personnel information.
Wherein the potential order data comprises a set of order accounts, order locations, order times, and order quantities for all potential orders. Likewise, the data of the orders to be preempted also includes the collection of the order placing account, the order placing position, the order placing time and the order placing quantity of all the orders to be preempted. The distribution personnel information includes distribution of all the distribution personnel, for example, distribution of quantity and distribution of location. The order supply and demand dispatching system can make a reasonable allocation strategy according to the distribution conditions of potential orders, orders to be preempted and distribution personnel to allocate the distribution personnel in advance, and can well solve the problem of sudden burst of order quantity.
Preferably, the potential order data includes time, quantity and location of the potential order, and the data for the order to be preempted includes time, quantity and location of the order to be preempted.
Preferably, the order supply and demand scheduling method further includes:
and displaying the distribution of the potential order data, the order data to be preempted and the distribution personnel information on the map in the form of thermodynamic diagrams.
Specifically, the distribution conditions of the potential orders, the orders to be preempted and the idle delivery personnel can be displayed in a thermodynamic diagram mode, in this embodiment, the thermodynamic diagram displays the orders to be preempted, the potential orders and the idle delivery personnel, the real-time display can be performed according to the number and the positions of the orders to be preempted, the potential orders and the idle delivery personnel, each completed order is extinguished (or changed in color) in the thermodynamic diagram, the ratio of the orders to be preempted and the potential orders to the idle delivery personnel in each delivery area can be visually displayed, and the delivery personnel can be timely deployed. In this embodiment, the dispatching of the delivery personnel can be performed through the background of the order supply and demand dispatching system, and when the background of the order supply and demand dispatching system is too late to perform dispatching of the delivery personnel and/or the delivery personnel cannot complete a delivery task, the customer service personnel can also quickly check the distribution conditions of the to-be-preempted orders, the potential orders and the idle delivery personnel displayed by the thermodynamic diagram, and send messages to the delivery personnel in time for emergency dispatching.
According to the method and the device, the potential order data and the data of the order to be preempted are obtained, and the dispatching personnel are dispatched according to the potential order data, the data of the order to be preempted and the dispatching personnel information, so that the possibility of the occurrence of an order bottleneck can be prevented and reduced, and the effects of predicting the outbreak of the order and reasonably dispatching the dispatching personnel to dispatch the order in advance are achieved.
Example two
Fig. 2 is a flowchart of an order supply and demand scheduling method in the second embodiment of the present invention, and the present embodiment performs further optimization based on the first embodiment. As shown in fig. 2, the method includes:
and S210, carrying out data mining on the historical order data and the preferential activity information, and predicting potential order data.
And S220, filtering the real-time order data and determining the order data to be preempted.
And S230, taking the sum of the number of the potential orders and the number of the orders to be preempted as an order demand, and determining the order demand in different time periods of each distribution area according to the time and the position of the potential orders and the orders to be preempted.
The order demand comprises the sum of the number of the potential orders and the number of the orders to be preempted, when the potential orders and the orders to be preempted are displayed, the potential orders and the orders to be preempted can be marked and displayed on a map in a thermodynamic diagram mode, namely, different display marks are adopted to visually and respectively display the orders to be preempted and the potential orders, so that the position distribution conditions corresponding to the potential orders and the orders to be preempted can be obviously seen on the map, meanwhile, the demand of the orders to be preempted and the potential orders needing to be delivered in each delivery area can be seen, the follow-up timely allocation according to the position distribution can be conveniently carried out, manpower and material resources are saved to a great extent, and the delivery time is shortened.
S240, calculating the allocation ratio of the number of the distribution personnel with the idle state to the order demand among the distribution personnel in different time periods of each distribution area.
Generally, the order demand and supply system divides the order delivery area according to a preset rule because the delivery range is wide. For example, the order demand and supply system may divide the distribution range into smaller distribution areas, which are: region 1, region 2, region 3, … …, region N-1, and region N. At this time, the order supply and demand scheduling system may calculate the number of the delivery staff in each of the areas 1 to N according to the positions of the delivery staff, judge the status of the delivery staff in each delivery area, mark the delivery staff in an idle state in each delivery area, and further calculate the allocation ratio of the number of the delivery staff in the idle state to the order demand.
Preferably, the allocation ratio of the number of idle state delivery persons to the order demand amount is the allocation ratio of the number of idle state delivery persons to the order demand amount in the corresponding delivery area in each delivery area.
For example, assuming that the number of idle dispatchers in area 2 is a, the number of orders to be preempted in area 2 is B, and the number of potential orders in area 2 is C, the allocation ratio of the number of idle dispatchers in area 2 to the order demand is the ratio of a to B + C, and the other areas are calculated in this way. The potential orders, the orders to be preempted and the distribution personnel can be displayed in a distinguishing way through a display mode, so that the distribution conditions of the potential orders, the orders to be preempted and the distribution personnel can be visually displayed, and in the same way, different display modes can be adopted for displaying different areas, for example, different colors are adopted for displaying different areas, different colors are adopted for marks of the potential orders, the orders to be preempted and the distribution personnel, and the like. Further, the allocation ratio of the number of idle state delivery persons to the order quantity demand may also be the allocation ratio of the number of idle state delivery persons in the whole delivery range to the order quantity demand in the corresponding delivery range, that is, the ratio of the total number of delivery persons in the N areas to the total number of order in the N areas.
And S250, determining hot spot areas and non-hot spot areas in different time periods of each distribution area according to the configuration ratio and a preset threshold.
Generally, since the number of the delivery areas is very large, in order to better and intuitively display which delivery areas need to be scheduled by delivery personnel, the N delivery areas need to be further classified into hot areas and non-hot areas. Specifically, the determination and the distinction can be performed according to the configuration ratio of the number of idle state delivery personnel to the order demand and the set threshold. For example, assuming that the number of delivery staff in an idle state in area 2 is a, the number of orders to be preempted in area 2 is B, and the number of potential orders in area 2 is C, the allocation ratio of the number of idle delivery staff in area 2 to the order demand is a/(B + C). According to the configuration ratio A/(B + C), a threshold D can be set, if the configuration ratio A/(B + C) is larger than the threshold D, the area 2 is considered to be a non-hot spot area, the order demand in the area 2 is small, the idle-state delivery personnel are sufficient, and the requirement delivery of orders can be met without dispatching the delivery personnel from other delivery areas; if the configuration ratio a/(B + C) is smaller than the threshold D, it is determined that the area 2 is a hot spot area, the order demand in the area 2 is large, and the number of idle delivery personnel is seriously insufficient, so that the order supply and demand scheduling system is required to perform personnel allocation. Other distribution areas can also be divided into hot spot areas and non-hot spot areas by referring to the division mode of the area 2, and the corresponding threshold value D needs to be set according to the specific actual conditions of the respective distribution areas so as to achieve the optimal division effect and carry out reasonable allocation. The threshold D may be a fixed value set in advance, or may be a variable value set in real time.
And S260, sending scheduling information to the delivery personnel in the non-hot spot area, wherein the delivery personnel is in an idle state, so that the delivery personnel can be allocated to the hot spot area close to the delivery personnel.
Specifically, in the foregoing step, hot spot areas and non-hot spot areas are divided into N distribution areas, and then distribution personnel need to be called into the hot spot areas according to the division of the hot spot areas and the non-hot spot areas. The method for dispatching the distribution personnel to the hot spot area can be that the dispatching information is sent to the distribution personnel in the idle state in the non-hot spot area, and the distribution personnel in the non-hot spot area close to the hot spot area are dispatched to the hot spot area according to the principle of proximity to the hot spot area to carry out order distribution.
Preferably, the dispatching personnel scheduling is performed according to the potential order data, the order data to be preempted and the dispatching personnel information, and the method further includes:
and activating delivery personnel in a hot spot area or a non-hot spot area adjacent to the hot spot area, wherein the delivery personnel is in a sleep state, and sending scheduling information so that the delivery personnel can be deployed to the hot spot area close to the delivery personnel.
Specifically, because the number of the distribution personnel in each distribution area is limited, when the demand for orders is particularly large, even if all the distribution personnel in the idle state in the non-hot spot area are allocated to the hot spot area, the demand for order distribution cannot be met, at this time, the distribution personnel in the sleep state in the hot spot area and/or the non-hot spot area close to the hot spot area need to be activated, and the allocation information is sent to the distribution personnel in the activated sleep state to distribute the orders. The delivery personnel in the sleep state may include delivery personnel who are registered in the order supply and demand system and occasionally perform part-time, such as those who normally perform part-time, generally do not perform delivery of orders, and perform a small amount of order delivery only occasionally out on the way, and the like, and may include official delivery personnel who are registered in the order supply and demand system, but may temporarily fail to perform delivery work while they are on vacation for some reason. Generally, main personal information is registered when the delivery personnel in the sleep state register, and when the delivery personnel in the sleep state need to deliver the order, the order supply and demand scheduling system can inform the delivery personnel in the sleep state of delivering the order by means of short messages, telephones, mails and the like.
According to the method and the device for dispatching the order, the potential order data and the order data to be preempted are obtained, and dispatching personnel are dispatched according to the potential order data, the order data to be preempted and the dispatching personnel information, so that the possibility of the appearance of an order bottleneck can be prevented and reduced, the outbreak of the order can be predicted in advance, the transport capacity is reasonably configured, the quick order-taking experience is improved, and the effects of increasing the order receiving quantity of the dispatching personnel and reducing the order flow rate are achieved.
EXAMPLE III
Fig. 3 is a schematic structural diagram of an order supply and demand scheduling system according to a third embodiment of the present invention, where the system executes the order supply and demand scheduling method provided in any one of the above embodiments, and the system may be implemented in a software and/or hardware manner. As shown in fig. 3, the system specifically includes:
the potential order prediction module 310 is configured to perform data mining on historical order data and preferential activity information to predict potential order data;
the to-be-preempted order acquisition module 330 is configured to filter the real-time order data and determine the to-be-preempted order data;
and a dispatching personnel dispatching module 320, configured to dispatch dispatching personnel according to the potential order data, the order data to be preempted, and the dispatching personnel information.
Preferably, the delivery person scheduling module 320 includes:
the order demand determining unit is used for taking the sum of the number of the potential orders and the number of the orders to be preempted as the order demand, and determining the order demand in different time periods of each distribution area according to the time and the position of the potential orders and the orders to be preempted;
the allocation ratio calculating unit is used for calculating the allocation ratio of the number of the distribution personnel with idle states to the order demand among the distribution personnel in different time periods of each distribution area;
the area dividing unit is used for determining hot spot areas and non-hot spot areas in different time periods of each distribution area according to the configuration ratio and a preset threshold;
and the allocation execution unit is used for sending scheduling information to the distribution personnel in the non-hot spot area, wherein the state of the distribution personnel is idle, so that the distribution personnel can allocate to the hot spot area close to the distribution personnel.
Further, the dispatching personnel scheduling module 320 further includes:
and the allocation activation unit is used for activating the delivery personnel in the hot spot area or the non-hot spot area adjacent to the hot spot area, wherein the delivery personnel is in a sleep state, and sending scheduling information so as to allocate the delivery personnel to the hot spot area close to the delivery personnel.
Preferably, the historical order data includes at least one of: order data of a hot spot area, order data of a large number of merchants and order data of high-frequency individual users.
Preferably, the potential order data includes time, quantity and position of the potential order, and the data for the order to be preempted includes time, quantity and position of the order to be preempted.
Preferably, the order supply and demand scheduling system further includes:
and the thermal display module is used for displaying the distribution situation of the potential order data, the order data to be preempted and the distribution personnel information on the map in a thermodynamic diagram mode.
According to the method and the device for dispatching the order, the potential order data and the order data to be preempted are obtained, and dispatching personnel are dispatched according to the potential order data, the order data to be preempted and the dispatching personnel information, so that the possibility of the appearance of an order bottleneck can be prevented and reduced, the outbreak of the order can be predicted in advance, the transport capacity is reasonably configured, the quick order-taking experience is improved, and the effects of increasing the order receiving quantity of the dispatching personnel and reducing the order flow rate are achieved.
Example four
Fig. 4 is a schematic structural diagram of an order demand and supply scheduling computer device in the fourth embodiment of the present invention. FIG. 4 illustrates a block diagram of an exemplary order supply and demand dispatch computer device 412 suitable for use in implementing embodiments of the present invention. The order supply and demand dispatch computer device 412 shown in FIG. 4 is only an example and should not impose any limitations on the functionality or scope of use of embodiments of the present invention.
As shown in FIG. 4, the order supply and demand dispatch computer device 412 is in the form of a general purpose computing device. The components of the order supply and demand dispatch computer device 412 may include, but are not limited to: one or more processors or processing units 416, a system memory 428, and a bus 418 that couples the various system components including the system memory 428 and the processing unit 416.
The order supply and demand dispatch computer device 412 typically includes a variety of computer system readable media. Such media can be any available media that can be accessed by the order supply and demand dispatch computer device 412 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 428 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)430 and/or cache memory 432. The order supply and demand dispatch computer device 412 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 434 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 418 by one or more data media interfaces. Memory 428 can include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 440 having a set (at least one) of program modules 442 may be stored, for instance, in memory 428, such program modules 442 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. The program modules 442 generally perform the functions and/or methodologies of the described embodiments of the invention.
The order on-demand dispatch computer device 412 may also communicate with one or more external devices 414 (e.g., keyboard, pointing device, display 424, etc.), with one or more devices that enable a user to interact with the order on-demand dispatch computer device 412, and/or with any devices (e.g., network card, modem, etc.) that enable the order on-demand dispatch computer device 412 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 422. Also, the order supply and demand dispatch computer device 412 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) through the network adapter 420. As shown, the network adapter 420 communicates with the other modules of the order supply and demand dispatch computer device 412 over a bus 418. It should be appreciated that although not shown in FIG. 4, other hardware and/or software modules may be used in conjunction with the computer device 412, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 416 executes various functional applications and data processing by running programs stored in the system memory 428, for example, implementing the order supply and demand scheduling method provided by the embodiment of the present invention, including:
data mining is carried out on historical order data and preferential activity information, and potential order data are predicted;
filtering the real-time order data to determine order data to be preempted;
and dispatching delivery personnel according to the potential order data, the order data to be preempted and the information of the delivery personnel.
EXAMPLE five
The fifth embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the order supply and demand scheduling method provided in the fifth embodiment of the present invention, where the method includes:
data mining is carried out on historical order data and preferential activity information, and potential order data are predicted;
filtering the real-time order data to determine order data to be preempted;
and dispatching delivery personnel according to the potential order data, the order data to be preempted and the information of the delivery personnel.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (8)
1. An order supply and demand scheduling method, characterized in that the method comprises:
data mining is carried out on historical order data and preferential activity information, and potential order data of each distribution area in different time periods are predicted; the historical order data includes at least one of: order data of a hotspot area, order data of a large number of merchants and order data of high-frequency individual users;
filtering the real-time order data to determine order data to be preempted;
taking the sum of the number of the potential orders and the number of the orders to be preempted as an order demand, and determining the order demand in different time periods of each distribution area according to the time and the position of the potential orders and the orders to be preempted;
calculating the allocation ratio of the number of the distribution personnel with idle states to the order demand among the distribution personnel in different time periods of each distribution area;
determining hot spot areas and non-hot spot areas in different time periods of each distribution area according to the configuration ratio and a preset threshold;
sending scheduling information to delivery personnel in a non-hot spot area, wherein the delivery personnel are idle, so that the delivery personnel can be allocated to a hot spot area close to the delivery personnel;
and activating delivery personnel in a hot spot area or a non-hot spot area adjacent to the hot spot area, wherein the delivery personnel is in a sleep state, and sending scheduling information so that the delivery personnel can be deployed to the hot spot area close to the delivery personnel.
2. The method of claim 1 wherein the potential order data comprises time, quantity, and location of potential orders and the to-be-preempted order data comprises time, quantity, and location of to-be-preempted orders.
3. The method of claim 1, further comprising:
and displaying the distribution of the potential order data, the order data to be preempted and the distribution personnel information on the map in the form of thermodynamic diagrams.
4. An order supply and demand dispatch system, the system comprising:
the potential order prediction module is used for carrying out data mining on historical order data and preferential activity information to predict potential order data; the historical order data includes at least one of: order data of a hotspot area, order data of a large number of merchants and order data of high-frequency individual users;
the order acquisition module to be preempted is used for filtering the real-time order data and determining the order data to be preempted;
the delivery personnel scheduling module is used for scheduling delivery personnel according to the potential order data, the order data to be robbed and the delivery personnel information; the delivery personnel scheduling module comprises: the order demand determining unit is used for taking the sum of the number of the potential orders and the number of the orders to be preempted as the order demand, and determining the order demand in different time periods of each distribution area according to the time and the position of the potential orders and the orders to be preempted; the allocation ratio calculating unit is used for calculating the allocation ratio of the number of the distribution personnel with idle states to the order demand among the distribution personnel in different time periods of each distribution area; the area dividing unit is used for determining hot spot areas and non-hot spot areas in different time periods of each distribution area according to the configuration ratio and a preset threshold; the allocation execution unit is used for sending scheduling information to the distribution personnel in the non-hot spot area, wherein the state of the distribution personnel is idle, so that the distribution personnel can allocate to the hot spot area close to the distribution personnel; and the allocation activation unit is used for activating the delivery personnel in the hot spot area or the non-hot spot area adjacent to the hot spot area, wherein the delivery personnel is in a sleep state, and sending scheduling information so as to allocate the delivery personnel to the hot spot area close to the delivery personnel.
5. The system of claim 4, wherein the potential order data comprises a time, a quantity, and a location of a potential order, and wherein the to-be-preempted order data comprises a time, a quantity, and a location of an order to be preempted.
6. The system of claim 4, further comprising:
and the thermal display module is used for displaying the distribution situation of the potential order data, the order data to be preempted and the distribution personnel information on the map in a thermodynamic diagram mode.
7. A computer device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the order supply and demand scheduling method of any one of claims 1-3.
8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the order supply and demand scheduling method according to any one of claims 1 to 3.
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