Logistics order distribution method and device, electronic equipment and computer readable storage medium

Abstract

The invention discloses a logistics order distribution method. The method comprises the steps that the unit logistics cost of each candidate logistics provider is acquired; when a preset updating condition is met, the constraint violation cost corresponding to each candidate logistics provider is updated, and the constraint violation cost comprises the lower limit constraint violation cost and the upper limit constraint violation cost; the latest constraint violation cost corresponding to the candidate logistics provider at the current moment is determined, the unit logistics cost of the candidate logistics provider is corrected according to the latest constraint violation cost, and the corrected unit cost for allocating the order to be allocated to the candidate logistics provider is obtained; and selecting a target logistics provider with the lowest correction unit cost from the candidate logistics providers, and determining the logistics providers allocated to the to-be-allocated order based on the target logistics provider. According to the logistics order distribution scheme, the comprehensive logistics cost can be lower, and the distribution timeliness of each logistics provider can be better ensured. The invention further provides a corresponding logistics order distribution device, electronic equipment and a computer readable storage medium.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of logistics, and in particular to a logistics order distribution method and device, an electronic device, and a computer readable storage medium. BACKGROUND

[0002] With the rapid development of computer and Internet technology, more and more users use online shopping platforms. When a user places an order to purchase goods on an online shopping platform, the platform usually needs to timely distribute packages to logistics operators.

[0003] In related technologies, when distributing packages to logistics operators, the packages are usually distributed to logistics operators with the lowest unit price and no order quantity notification in order to reduce logistics costs as much as possible.

[0004] However, different logistics operators usually have different cycle discount order quantities. For example, the cycle discount order quantity of a certain logistics operator is 1000 orders per month and less than 2000 orders, and the logistics unit price is 8 times. Among them, 2000 orders is usually the discount upper limit set by the logistics operator according to its logistics capacity, which means that when the logistics order quantity is too large, the logistics operator cannot deliver normally, so the discount order quantity upper limit is set to ensure normal delivery. The related technology of preferentially distributing packages to logistics operators with the lowest unit price may result in an order quantity that does not meet the cycle discount standard for other logistics operators, thereby increasing logistics costs, or may result in an order quantity that is too large for the logistics operator with the lowest unit price, thereby affecting delivery efficiency. SUMMARY

[0005] The present application provides a logistics order distribution method and device, an electronic device, and a computer readable storage medium, which can better meet the upper and lower limits of the cycle discount order quantity of each logistics operator, thereby reducing the comprehensive logistics cost and better ensuring the delivery efficiency of each logistics operator. The specific scheme is as follows:

[0006] In a first aspect, the present application provides a logistics order distribution method, which comprises:

[0007] obtaining the unit logistics cost of each candidate logistics operator;

[0008] when a preset update condition is met, updating the constraint violation cost corresponding to each candidate logistics operator, the constraint violation cost comprising a lower limit constraint violation cost and an upper limit constraint violation cost, the lower limit constraint violation cost being used to represent the increased logistics cost when the order quantity in the corresponding cycle is lower than the cycle discount lower limit of the candidate logistics operator, and the upper limit constraint violation cost being used to represent the increased logistics cost when the order quantity in the corresponding cycle is higher than the cycle discount upper limit of the candidate logistics operator;

[0009] determine a latest constraint violation cost corresponding to the candidate logistics provider at a current time, and correct the unit logistics cost of the candidate logistics provider according to the latest constraint violation cost, to obtain a corrected unit cost of assigning the to-be-assigned order to the candidate logistics provider;

[0010] select a target logistics provider with the lowest corrected unit cost from the candidate logistics providers, and determine the logistics provider to which the to-be-assigned order is assigned based on the target logistics provider.

[0011] In a second aspect, the present application provides a logistics order distribution device, which comprises:

[0012] an acquisition unit configured to acquire a unit logistics cost of each candidate logistics provider;

[0013] an updating unit configured to update a constraint violation cost corresponding to each candidate logistics provider when a preset updating condition is met, the constraint violation cost comprising a lower limit constraint violation cost and an upper limit constraint violation cost, the lower limit constraint violation cost being used to represent an increased logistics cost when an order quantity in a corresponding period is lower than a lower limit of a period discount of the candidate logistics provider, and the upper limit constraint violation cost being used to represent an increased logistics cost when the order quantity in the corresponding period is higher than an upper limit of the period discount of the candidate logistics provider;

[0014] a determination unit configured to determine a latest constraint violation cost corresponding to the candidate logistics provider at a current time, and correct the unit logistics cost of the candidate logistics provider according to the latest constraint violation cost, to obtain a corrected unit cost of assigning the to-be-assigned order to the candidate logistics provider;

[0015] a selection unit configured to select a target logistics provider with the lowest corrected unit cost from the candidate logistics providers, and determine the logistics provider to which the to-be-assigned order is assigned based on the target logistics provider.

[0016] In a third aspect, the present application further provides an electronic device, which comprises a processor, a memory, and computer program instructions stored in the memory and executable on the processor; the processor implements the method of the first aspect when executing the computer program instructions.

[0017] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer execution instructions, the computer execution instructions being used to implement the method of the first aspect when executed by a processor.

[0018] In a fifth aspect, an embodiment of the present application provides a computer program product, which comprises a computer program, the computer program being used to implement the method of the first aspect when executed by a processor.

[0019] Compared with the prior art, the present application has the following advantages:

[0020] The logistics order distribution method provided by the embodiment of the present application obtains the unit logistics cost of each candidate logistics provider, and updates the corresponding constraint violation cost of each candidate logistics provider when a preset update condition is met, wherein the constraint violation cost includes a lower limit constraint violation cost and an upper limit constraint violation cost. Since the lower limit constraint violation cost is used to represent the increased logistics cost when the order quantity in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider, and the upper limit constraint violation cost is used to represent the increased logistics cost when the order quantity in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider, the constraint violation cost can well reflect the marginal cost increased by violating the upper and lower limits of the period discount of the candidate logistics provider. Through the constraint violation cost, the order distribution can be better guided to meet the upper and lower limits of the period discount of the candidate logistics provider. The latest constraint violation cost corresponding to the candidate logistics provider at the current time is determined, which is the constraint violation cost obtained by the last update. The unit logistics cost of the candidate logistics provider is corrected according to the latest constraint violation cost, and the corrected unit cost of distributing the to-be-distributed order to the candidate logistics provider is obtained. The target logistics provider with the lowest corrected unit cost is selected from each candidate logistics provider, and the logistics provider to which the to-be-distributed order is distributed is determined based on the target logistics provider. Since the corrected unit cost is corrected by the latest constraint violation cost, the corrected unit cost can better reflect whether the order distribution meets the period discount order quantity of the candidate logistics provider, so that the target logistics provider determined according to the corrected unit cost is the logistics provider with the lowest cost under the premise of considering the upper and lower limits of the period discount order quantity of each candidate logistics provider, which can better meet the upper and lower limits of the period discount order quantity of each logistics provider, make the comprehensive logistics cost lower, and better guarantee the delivery time of each logistics provider.

[0021] Since the actual order quantity distributed to different candidate logistics providers changes in real time, the relationship between the order quantity distributed to each candidate logistics provider and the upper and lower limits of the period discount order quantity of the candidate logistics provider also changes constantly. The present application dynamically updates the corresponding constraint violation cost of each candidate logistics provider whenever the preset update condition is met, so that the corresponding constraint violation cost of the candidate logistics provider can be updated constantly according to the actual order distribution situation and better match the current order distribution situation, so that the order distribution decision is always based on the latest data rather than outdated information, and the discount order quantity target of the entire discount period can be better guaranteed not to be destroyed by short-term order distribution decisions. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 is an application scenario diagram of the scheme provided by the present application;

[0023] Figure 2 is a flowchart of an example of the logistics order distribution method provided by the embodiment of the present application;

[0024] Figure 3 is a structural block diagram of a logistics singling device provided in an embodiment of the present application;

[0025] Figure 4 is a structural schematic diagram of a logistics singling system provided in an embodiment of the present application;

[0026] Figure 5 is a structural block diagram of an electronic device provided in the present application. DETAILED DESCRIPTION

[0027] In order for those skilled in the art to better understand the technical solutions of the present application, the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. However, the present application can be implemented in many other ways different from the description below, and therefore, all other embodiments obtained by those skilled in the art based on the embodiments provided in the present application without creative labor should belong to the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", "third", and the like in the claims, the specification and the drawings of the present application are used to distinguish similar objects, and are not intended to describe a specific order or sequence. The data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described in the present application. In addition, the terms "include", "have" and their variants are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] It should be understood that in the embodiments of the present application, "at least one" means one or more, and "multiple" means two or more. "And / or" is only a description of the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects. "Including A, B and / or C" means including any one or any two or three of A, B and C.

[0030] It should be understood that in the embodiments of the present application, "B corresponding to A", "B corresponding to A", "A corresponding to B" or "B corresponding to A" means that B is associated with A, and B can be determined according to A. Determining B according to A does not mean that B is determined only according to A, but B can also be determined according to A and / or other information.

[0031] In order to facilitate the understanding of the embodiments of the present application, the application background of the embodiments is described.

[0032] With the rapid development of computer and Internet technology, more and more users use online shopping platforms. When users place orders to purchase goods on online shopping platforms, the platform usually needs to timely distribute packages to logistics operators.

[0033] In related technologies, when distributing packages to logistics merchants, the packages are usually distributed to logistics merchants with the lowest unit price and no order quantity notification, so as to reduce logistics costs as much as possible.

[0034] However, since different logistics merchants usually have different cycle discount order quantities, for example, the cycle discount order quantity of a certain logistics merchant is 8 times the logistics unit price when the monthly order quantity is greater than 1000 and less than 2000, wherein 2000 is usually the discount upper limit set by the logistics merchant according to its logistics capacity, indicating that the logistics merchant cannot normally deliver when the logistics order quantity is too large, so the discount order quantity upper limit is set to ensure normal delivery. The related technology of preferentially distributing packages to logistics merchants with the lowest unit price may result in an order quantity that does not meet the cycle discount standard for other logistics merchants, thereby increasing logistics costs, or may result in an order quantity that is too large for the logistics merchant with the lowest unit price, thereby affecting delivery timeliness.

[0035] To solve the above problems, the embodiments of the present application provide a logistics order distribution method and device, electronic equipment and computer readable storage medium. The purpose is to better meet the upper and lower limits of the cycle discount order quantity of each logistics merchant, so as to make the comprehensive logistics cost lower, and better guarantee the delivery timeliness of each logistics merchant.

[0036] The logistics order distribution method provided by the present application can be used for logistics order distribution of user ordered goods in e-commerce platforms, and can also be used for logistics order distribution in other scenarios, such as bulk procurement, logistics platforms for order distribution, etc. The present application does not make specific limitations.

[0037] In order to facilitate the understanding of the method embodiments of the present application, the application scenarios thereof are introduced. Please refer to Figure 1 , Figure 1 The application scenario of the scheme provided by the embodiments of the present application is shown in the figure. The application scenario is a schematic example and does not constitute a specific description of the application scenario. As Figure 1 shown, the application scenario is provided with a server 102 and a client 101. In this embodiment, the client 101 and the server 102 establish a connection through network communication to perform data transmission.

[0038] The client 101 can be a mobile phone, a tablet computer, a smart watch, a desktop computer, a smart television, a VR device, a vehicle-mounted device, a wearable device, a notebook computer, or the like electronic device having a display function and a data processing function. The client 101 is configured to acquire and display e-commerce page data from the server 102, determine a target commodity as a to-be-assigned order in response to a purchase operation of the target commodity triggered by a user on an e-commerce page, and send information of the to-be-assigned order to the server 102. The client 101 can also be configured to send an access request, interactive information, or the like to the server 102, so that the server 102 sends corresponding request data to the client 101 for display.

[0039] The server 102 has high computing capability. The server 102 can be a server, and the server 102 has high CPU computing capability, long-time reliable operation, strong I / O external data throughput capability, and better scalability. The server 102 can be a single server or a server cluster. The server 102 is configured to assign a logistics provider to a to-be-assigned order by a logistics order assignment method. The server 102 can also provide other specific services for the client 101, such as user information access, website access, application program access, or the like, which are not specifically limited in the present application.

[0040] The client 101 and the server 102 can communicate with each other by using various communication systems, such as a wired communication system or a wireless communication system. The wireless communication system can be, for example, a global system for mobile communications (GSM) system, a code division multiple access (CDMA) system, a wideband code division multiple access (WCDMA) system, a general packet radio service (GPRS), a long term evolution (LTE) system, an LTE frequency division duplex (FDD) system, an LTE time division duplex (TDD), a universal mobile telecommunication system (UMTS), a worldwide interoperability for microwave access (WiMAX) communication system, a future 5th generation (5G) system or new radio (NR), a satellite communication system, or the like.

[0041] Embodiment One

[0042] The first embodiment of the present application provides a logistics order processing method, which is applied to an electronic device. The electronic device can be a server, a desktop computer, a notebook computer, a smart television, a VR device, a vehicle-mounted device, a wearable device, a mobile phone, a tablet computer, a smart watch, or any other electronic device with data processing function.

[0043] As shown in Figure 2 The logistics order processing method provided by the first embodiment of the present application includes the following steps S110-S140.

[0044] Step S110: Obtain the unit logistics cost of each candidate logistics provider.

[0045] The unit logistics cost can be a logistics price per unit weight of the goods, a logistics price per piece of the goods, or a logistics price per unit volume of the goods. In actual applications, since the logistics providers usually set a first weight price and a subsequent weight price, the unit logistics cost can be an average unit cost of the candidate logistics provider, for example, the unit logistics cost can be an average unit weight price, an average single-piece price, or an average unit volume price of the candidate logistics provider, and the like, which are not specifically limited in the present application. In the embodiments of the present application, the unit logistics cost of each candidate logistics provider can be obtained according to the bidding information of each candidate logistics provider.

[0046] Step S120: updating the constraint violation cost corresponding to each candidate logistics provider when a preset updating condition is met, the constraint violation cost including a lower limit constraint violation cost and an upper limit constraint violation cost, the lower limit constraint violation cost being used to represent an increased logistics cost when the order quantity in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider, and the upper limit constraint violation cost being used to represent an increased logistics cost when the order quantity in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider.

[0047] The above-mentioned preset updating condition can include at least one of the following: reaching a preset time interval point, generating a new to-be-allocated order, completing the allocation of a to-be-allocated order, and reaching a preset number interval of completed allocated orders. The preset time interval can be any interval in a range from 30 minutes to 2 hours.

[0048] When the preset updating condition includes reaching a preset time interval point, the constraint violation cost corresponding to each candidate logistics provider is updated every time the preset time interval point is reached, for example, the constraint violation cost corresponding to each candidate logistics provider is updated once every 30 minutes. The updating of the constraint violation cost according to the time interval point can timely update the constraint violation cost according to the latest order and logistics data, and will not cause excessive consumption of system resources due to too frequent updating. When the preset updating condition includes generating a new to-be-allocated order, the constraint violation cost corresponding to each candidate logistics provider is updated if a new to-be-allocated order is generated. In this way, the cost data required for the allocation decision can be timely adjusted when a new order appears. When the preset updating condition includes completing the allocation of a to-be-allocated order, the constraint violation cost is updated after completing an allocation operation, so that the subsequent allocation decision is based on the latest allocation result. When the preset updating condition includes reaching a preset number interval of completed allocated orders, for example, the constraint violation cost is updated once every 100 allocated orders. In this way, the cost data can be timely updated when the number of allocated orders reaches a certain scale, so that the constraint violation cost can be timely updated according to the change of the number of allocated orders, and will not cause excessive consumption of system resources due to too frequent updating. Those skilled in the art can select a suitable updating condition according to actual conditions, which is not specifically limited in the present application.

[0049] For the lower limit violation constraint cost, if the number of orders allocated to a candidate logistics provider in the corresponding period is lower than the lower limit of its period discount, a certain calculation rule is used to increase the corresponding logistics cost, for example, if the lower limit of a logistics provider's period discount is 100 orders, only 80 orders are allocated in the current period, and the lower limit violation constraint cost is calculated according to the difference between the two and the relevant cost coefficient of the logistics provider. For the upper limit violation constraint cost, if the number of orders allocated to a candidate logistics provider in the corresponding period is higher than the upper limit of its period discount, the increased logistics cost is also calculated according to the excess order quantity and the relevant cost coefficient. By dynamically updating the violation constraint cost in this way, the corresponding violation constraint cost of the candidate logistics provider can always be closely matched with the actual order allocation. Then, in the subsequent order allocation process, the unit logistics cost of the candidate logistics provider is corrected based on the updated violation constraint cost, and a more accurate corrected unit cost is obtained. In this way, when selecting the target logistics provider, the period discount order quantity upper and lower limits of each candidate logistics provider can be more accurately considered, the comprehensive logistics cost can be further reduced, and the delivery timeliness of each logistics provider can be better guaranteed.

[0050] The lower limit violation constraint cost is used to measure the additional logistics cost when the order quantity in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider. It reflects the additional cost due to the lack of order quantity to enjoy the discount. For example, for the lower limit violation constraint cost, if the lower limit of a candidate logistics provider's period discount is 500 orders per month, and the number of orders allocated to the logistics provider in the current period is only 300 orders, since the discount lower limit is not reached, the logistics cost cannot be calculated according to the discount price, resulting in additional logistics cost. This additional logistics cost is the lower limit violation constraint cost.

[0051] The logistics provider usually sets a period discount upper limit to avoid too many orders exceeding the capacity. Exceeding this upper limit may affect the delivery timeliness or even prevent normal delivery. The upper limit violation constraint cost is used to measure the additional cost when the order quantity in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider. For example, if a logistics provider's period discount upper limit is 2000 orders per month, and the number of orders allocated to the logistics provider in the current period reaches 2200 orders, the additional 200 orders may require additional resources to ensure delivery, such as increasing transportation vehicles or temporarily hiring more delivery personnel. Therefore, the additional 200 orders cannot enjoy the discount, and the additional cost generated thereby is the upper limit violation constraint cost.

[0052] The calculation period of the period discount of the logistics provider can be one month, half a month, one week, etc. In general, the discount calculation period is one month. In this case, the period discount lower limit is the monthly discount lower limit, and the period discount upper limit is the monthly discount upper limit.

[0053] By dynamically updating the lower limit violation constraint cost and the upper limit violation constraint cost, the actual situation of each candidate logistics provider can be considered in the subsequent logistics order distribution process. In this way, when selecting a target logistics provider for a to-be-assigned order, not only the unit logistics cost is considered, but also the modified unit cost, i.e., the cost after considering the violation constraint cost, so as to reduce the comprehensive logistics cost on the basis of meeting the upper and lower limits of the cycle discount order quantity of each logistics provider, while ensuring that each logistics provider can complete order distribution on time and efficiently, and improving the efficiency and service quality of the entire logistics distribution system.

[0054] In an embodiment, when updating the violation constraint cost, the updated violation constraint cost can be calculated according to the relationship between the actual order quantity assigned to each candidate logistics provider in the current cycle and the cycle discount upper and lower limit corresponding to the candidate logistics provider. Specifically, the updated violation constraint cost can be calculated based on the principle of minimizing the total logistics cost and according to the relationship between the actual order quantity assigned to each candidate logistics provider in the current cycle and the cycle discount upper and lower limit corresponding to the candidate logistics provider.

[0055] In a specific embodiment, the violation constraint cost can be updated in the following steps S121-S122.

[0056] Step S121: determining a stage order distribution constraint condition corresponding to the candidate logistics provider in the current update stage according to the lower limit and the upper limit of the cycle discount order quantity of the candidate logistics provider, the stage order distribution constraint condition being used to represent an order quantity distribution interval satisfied by the order quantity assigned to the candidate logistics provider in the current update stage.

[0057] Specifically, the stage order distribution constraint condition corresponding to the current update stage can be determined according to the assigned logistics order quantity in the current cycle and the cycle discount upper and lower limit of the candidate logistics provider according to the time proportion.

[0058] Specifically, the current cycle can be divided into multiple update stages, and each stage corresponds to a certain time proportion. For example, if one month is a cycle and one update stage is 1 hour. According to the current update stage, the cycle discount upper and lower limit of the candidate logistics provider, and the assigned logistics order quantity in the current cycle, the order quantity constraint interval corresponding to the stage is determined according to the time proportion, which is the above-mentioned stage order distribution constraint condition. Assuming that the monthly discount lower limit of a candidate logistics provider is 10000 orders, the upper limit is 20000 orders, the assigned logistics order quantity this month is 3000 orders, and the current time is the second hour of the 10th day, then according to the time proportion, the order quantity lower limit corresponding to the stage is about (10000-3000) ÷ 20 ÷ 24≈15 orders, and the upper limit is about (20000-3000) ÷ 20 ÷ 24≈35 orders, i.e., the order quantity constraint interval of the stage can be 15-35.

[0059] Step S122: determining the constraint violation cost of the corresponding candidate logistics provider in the current update stage according to the stage-based single assignment constraint condition.

[0060] Specifically, the updated constraint violation cost corresponding to the current update stage can be obtained according to the stage-based single assignment constraint condition corresponding to the current update stage, the order quantity of the current update stage, and based on the principle of minimizing the total logistics cost of the current update stage.

[0061] Specifically, the order quantity of the current update stage can be determined according to the generated order quantity and the predicted order quantity of the current stage. The total logistics cost of the current update stage can be determined according to the order quantity constraint interval corresponding to the current update stage and the order quantity of the current update stage, and the updated constraint violation cost corresponding to the current update stage can be obtained based on the principle of minimizing the total logistics cost of the current update stage.

[0062] In one specific embodiment, the lower limit constraint violation cost can be represented by a lower limit dual value, and the upper limit constraint violation cost can be represented by an upper limit dual value. The lower limit dual value is a dual value that violates the condition that the order quantity in the corresponding period is greater than the discount lower limit of the candidate logistics provider, and the upper limit dual value is a dual value that violates the condition that the order quantity in the corresponding period is less than the discount upper limit of the candidate logistics provider.

[0063] The dual value is a numerical value that measures the tightness of the constraint condition. By using the lower limit dual value and the upper limit dual value to represent the lower limit constraint violation cost and the upper limit constraint violation cost, the constraint condition in logistics single assignment and the cost calculation can be linked, which facilitates the use of optimization algorithms to obtain the dual value, so that the updated constraint violation cost can be easily obtained.

[0064] In practical applications, a linear programming model can be constructed to calculate the dual value. The objective of this linear programming model is to minimize the total logistics cost of the current update stage, and its constraint conditions include the order quantity constraint interval of each candidate logistics provider and other related logistics order constraints. By solving this linear programming model, the lower limit dual value and the upper limit dual value can be obtained, and then the updated lower limit constraint violation cost and the updated upper limit constraint violation cost can be obtained.

[0065] When solving the linear programming model, solvers in related technologies can be used to calculate the dual value, such as CPLEX, Gurobi, Solving Constraint Integer Programs (SCIP), etc. These solvers have high computing power and can obtain accurate dual values in a short time.

[0066] Specifically, the solver can be used to solve the dual value corresponding to the order quantity constraint interval of the current update stage by means of mixed integer programming, so as to determine the solved dual value as the updated violation constraint cost corresponding to the current update stage.

[0067] The minimum total logistics cost of the current update stage can be represented by the following formula (1).

[0068]

[0069] wherein x ijt represents the quantity of order i allocated to logistics provider j at time t, I is the order set, J is the candidate logistics provider set, T is the time set of the current update stage, c ij is the unit cost of allocating order i to logistics provider j.

[0070] The constraint condition for solving the dual value by formula (1) is the order quantity constraint interval corresponding to the current update stage, that is, the constraint condition for solving the dual value by the following formula (2).

[0071]

[0072] wherein U j represents the upper limit of the order quantity constraint interval corresponding to the current update stage, and L j represents the lower limit of the order quantity constraint interval corresponding to the current update stage.

[0073] In the embodiment, the dual value corresponding to the order quantity constraint interval of the current update stage includes the lower limit dual value q j and the upper limit dual value p j , the lower limit dual value q j is the dual value corresponding to the lower limit of the order quantity constraint interval of the previous update stage, and represents the cost increased when the lower limit of the order quantity constraint interval is exceeded, and the upper limit dual value p j is the dual value corresponding to the upper limit of the order quantity constraint interval of the previous update stage, and represents the cost increased when the upper limit of the order quantity constraint interval is exceeded.

[0074] When solving the dual value, the variable x ijt can be linearly relaxed (x ijt ≤1 corresponds to the dual variable y ijt ≥0), to obtain the dual solution process of solving the minimum total logistics cost of the current update stage, and the lower limit dual value q j and the upper limit dual value p j are determined by the following formula (3).

[0075]

[0076] wherein d i ∈R, d i represents the dual variable corresponding to the constraint that each order i must and can only be assigned to one logistics provider at each time t.

[0077] The above formulas (1), (2) can be used to build a mixed integer programming problem, and a solver is used to solve the preferred solution corresponding to the dual value, that is, the lower limit dual value q j and the upper limit dual value p j of formula (3) can be solved.

[0078] The present embodiment uses the dual value to represent the violation constraint cost, combines the linear programming model and the solver for calculation, so that the cost calculation is more accurate and efficient.

[0079] After determining the stage-by-stage order allocation constraint condition, the present embodiment can determine the order allocation range of each candidate logistics provider in the current update stage, so that the order allocation process is more scientific and reasonable, and the violation constraint cost determined based on the stage-by-stage order allocation constraint condition can provide a more accurate cost basis for logistics order allocation decision. The stage-by-stage method can also enhance the flexibility and adaptability of the logistics order allocation system. By continuously updating the violation constraint cost and the stage-by-stage order allocation constraint condition, the logistics order allocation system can adapt to these changes in time and always maintain high order allocation efficiency.

[0080] Step S130: determining the latest violation constraint cost corresponding to the candidate logistics provider at the current time, and correcting the unit logistics cost of the candidate logistics provider according to the latest violation constraint cost to obtain a corrected unit cost of assigning the to-be-allocated order to the candidate logistics provider.

[0081] The latest violation constraint cost corresponding to the candidate logistics provider at the current time is the large violation constraint cost updated in the most recent update stage.

[0082] When the unit logistics cost of the candidate logistics provider is corrected, the unit logistics cost can be added to a marginal cost to obtain a corrected unit cost, where the marginal cost is positively correlated with the upper limit violation constraint cost and negatively correlated with the lower limit violation constraint cost. The marginal cost is positively correlated with the upper limit violation constraint cost because when the order quantity exceeds the upper limit, the additional order quantity cannot enjoy the discounted logistics unit price, which will cause the cost to increase, so the marginal cost will increase with the increase of the upper limit violation constraint cost. The marginal cost is negatively correlated with the lower limit violation constraint cost because when the order quantity is lower than the lower limit, the discount cannot be enjoyed due to not reaching the discount lower limit, in which case the more subsequent allocated order quantity, the closer to the discount lower limit, and the lower the unit cost. When the marginal cost is positively correlated with the upper limit violation constraint cost and negatively correlated with the lower limit violation constraint cost, the corrected unit cost can be simply and conveniently obtained, and the corrected unit cost can more accurately reflect the actual cost of allocating the to-be-allocated order to the candidate logistics provider.

[0083] Specifically, the marginal cost can be the difference between the upper limit violation constraint cost and the lower limit violation constraint cost, that is, the marginal cost is c ij + p j - q j represents the corrected unit cost of allocating the to-be-allocated order to the candidate logistics provider.

[0084] Alternatively, the upper limit violation constraint cost and the lower limit violation constraint cost can also be assigned a weight coefficient, and the weight coefficient represents the degree of influence of being less than the lower limit and being greater than the upper limit on the cost. The corrected unit cost is determined according to the lower limit violation constraint cost, the upper limit violation constraint cost, and the respective assigned weight coefficient.

[0085] Step S140: selecting a target logistics provider with the lowest corrected unit cost from the candidate logistics providers, and determining the logistics provider to which the to-be-allocated order is allocated based on the target logistics provider.

[0086] Specifically, the target logistics provider can be determined as the logistics provider to which the to-be-allocated order is allocated, so as to simply and conveniently determine the logistics provider to which the to-be-allocated order is allocated.

[0087] In an embodiment, step S140 can be implemented in the following steps S141-S142.

[0088] Step S141: when the transportation quantity of the target logistics provider in the current period does not reach a preset threshold, determining the target logistics provider as the logistics provider to which the to-be-allocated order is allocated.

[0089] The preset threshold is an upper limit value of the periodic capacity of the target logistics provider. When the transportation volume of the target logistics provider in the current period does not reach the preset threshold, it indicates that the capacity of the target logistics provider still has a margin, and therefore, the target logistics provider can be determined as the logistics provider to which the to-be-allocated order is allocated.

[0090] Step S142: When the transportation volume of the target logistics provider in the current period reaches the preset threshold, a sub-target logistics provider whose modified unit cost is higher than that of the target logistics provider is selected from the candidate logistics providers, and the logistics provider to which the to-be-allocated order is allocated is determined based on the sub-target logistics provider.

[0091] When the transportation volume of the target logistics provider in the current period reaches the preset threshold, it indicates that the capacity of the target logistics provider in the current period is insufficient. In this case, continuously allocating orders to the target logistics provider may cause problems such as delay in logistics distribution, decline in service quality, and out-of-stock. Therefore, a sub-target logistics provider whose modified unit cost is higher than that of the target logistics provider needs to be selected from the candidate logistics providers. Specifically, the candidate logistics providers can be sorted in ascending order of the modified unit cost. When the capacity of the target logistics provider is insufficient, the next logistics provider in the sorted order is selected as the sub-target logistics provider. After the sub-target logistics provider is determined, the capacity of the sub-target logistics provider in the current period also needs to be considered. If the transportation volume of the sub-target logistics provider in the current period does not reach its preset threshold, the sub-target logistics provider can be determined as the logistics provider to which the to-be-allocated order is allocated. If the transportation volume of the sub-target logistics provider in the current period also reaches the preset threshold, other candidate logistics providers are selected in turn according to the sorted order of the modified unit cost, until a logistics provider whose transportation volume does not reach the preset threshold is found.

[0092] When the modified unit cost of the candidate logistics provider is determined by c ij +p j -q j When the modified unit cost of the candidate logistics provider is determined by c

[0093]

[0094] wherein, represents that the current order volume of the logistics provider j does not exceed the capacity threshold U j .

[0095] The logistics order distribution method provided by the embodiments of the present application obtains the unit logistics cost of each candidate logistics provider, and updates the constraint violation cost corresponding to each candidate logistics provider when a preset update condition is met, wherein the constraint violation cost includes a lower limit constraint violation cost and an upper limit constraint violation cost. Since the lower limit constraint violation cost is used to represent the increased logistics cost when the order quantity in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider, and the upper limit constraint violation cost is used to represent the increased logistics cost when the order quantity in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider, the constraint violation cost can well reflect the marginal cost increased by violating the upper and lower limits of the period discount of the candidate logistics provider. Through the constraint violation cost, the order distribution can be better guided to meet the upper and lower limits of the period discount of the candidate logistics provider. Then, the latest constraint violation cost corresponding to the candidate logistics provider at the current time is determined, which is the constraint violation cost obtained by the last update. The unit logistics cost of the candidate logistics provider is corrected according to the latest constraint violation cost, and the corrected unit cost of distributing the to-be-distributed order to the candidate logistics provider is obtained. The target logistics provider with the lowest corrected unit cost is selected from the candidate logistics providers, and the logistics provider to which the to-be-distributed order is distributed is determined based on the target logistics provider. Since the corrected unit cost is corrected by the latest constraint violation cost, the corrected unit cost can better reflect whether the order distribution meets the period discount order quantity of the candidate logistics provider, so that the target logistics provider determined according to the corrected unit cost is the logistics provider with the lowest cost under the premise of considering the upper and lower limits of the period discount order quantity of each candidate logistics provider, which can better meet the upper and lower limits of the period discount order quantity of each logistics provider, so that the comprehensive logistics cost is lower, and the delivery timeliness of each logistics provider is better guaranteed.

[0096] Since the actual order quantity distributed to different candidate logistics providers changes in real time, the relationship between the order quantity distributed to each candidate logistics provider and the upper and lower limits of the period discount order quantity of the candidate logistics provider also changes constantly. The embodiments of the present application dynamically update the constraint violation cost corresponding to each candidate logistics provider whenever the preset update condition is met, so that the constraint violation cost corresponding to the candidate logistics provider can be updated constantly according to the actual order distribution situation and better match the current order distribution situation, so that the order distribution decision is always based on the latest data rather than outdated information, and the discount order quantity target of the entire discount period can be better guaranteed not to be destroyed by short-term order distribution decisions.

[0097] In an embodiment, the above step S121 can determine the stage order distribution constraint condition corresponding to the candidate logistics provider in the current update stage according to the following steps S121a-S121b.

[0098] Step S121a: determining a monthly order quantity distribution interval of the candidate logistics provider according to the lower limit and the upper limit of the period discount order quantity corresponding to the candidate logistics provider.

[0099] Each update stage of the constraint violation cost is less than one month.

[0100] When the period discount order quantity corresponding to the candidate logistics provider is a monthly discount order quantity, the monthly order quantity distribution interval of the candidate logistics provider can be an interval formed by the lower limit and the upper limit of the monthly discount order quantity. When the period discount order quantity corresponding to the candidate logistics provider is a quarterly discount order quantity, the monthly order quantity distribution interval can be determined according to the lower limit and the upper limit of the quarterly discount order quantity, combined with the order quantity estimation of each month in the current quarter. For example, if the order quantity in the early stage of an order in a quarter is relatively small, the lower limit of the order quantity distribution of the first month can be reduced, and the upper limit of the order quantity distribution of the third month can be increased.

[0101] In the embodiments of the present application, the monthly order quantity distribution interval of the current month can be determined once every other month, that is, the determination of the monthly order quantity distribution interval is performed according to a time interval of one month, so that the monthly order quantity distribution interval of each month is more real-time. In a specific embodiment, step S121a can determine the monthly order quantity distribution interval according to the following steps A-B.

[0102] Step A: Obtain distribution reference information, the distribution reference information including at least one of historical order distribution data, future order quantity prediction data, and order target.

[0103] The historical order distribution data can include at least one of order distribution information of each candidate logistics provider in a preset historical time period, order distribution information of different time periods, and distribution efficiency of each candidate logistics provider. The future order quantity prediction data is a predicted monthly order quantity, which can be estimated based on order growth information, monthly promotion activity information, and other factors, which helps to plan logistics distribution in advance and avoid the situation of too many or too few orders of a logistics provider. The order target can be a target order quantity preset by the online shopping platform.

[0104] Step B: Determine the monthly order quantity distribution interval of the candidate logistics provider according to the distribution reference information and the lower limit and the upper limit of the period discount order quantity of the candidate logistics provider.

[0105] In the determination of the monthly single quantity distribution interval, the distribution reference information and the lower limit and upper limit of the candidate logistics company cycle discount single quantity are comprehensively considered to determine the monthly single quantity distribution interval, which can make the determined monthly single quantity distribution interval more reasonable and accurate. For example, if the historical single distribution data shows that a certain candidate logistics company has high delivery efficiency in a certain time period, and the future single quantity prediction data shows that the order quantity in this time period will increase, and the order target also requires a certain amount of order delivery in this time period, then when determining the monthly single quantity distribution interval of the candidate logistics company, the upper limit value can be appropriately increased. For future single quantity prediction data, if the order quantity is estimated to increase significantly based on order growth information and monthly promotion information, etc., the monthly single quantity distribution interval of each candidate logistics company needs to be adjusted accordingly, for example, a large-scale promotion activity is held on a certain online shopping platform this month, and it is estimated that the order quantity will increase by 50% than usual, at this time, the upper limit of the monthly single quantity distribution interval of each candidate logistics company needs to be increased according to their actual situation to cope with the possible increase in order quantity.

[0106] Step S121b: determining the stage single distribution constraint condition corresponding to the candidate logistics company in the current update stage based on the monthly single quantity distribution interval corresponding to the candidate logistics company.

[0107] Since each update stage is less than one month, the monthly single quantity distribution interval can be further refined to the current update stage. Specifically, the stage single distribution constraint condition corresponding to the current update stage can be obtained by distributing the single quantity according to the time proportion of each update stage in the month and combining the historical fluctuation rule of the order.

[0108] The embodiment first determines the monthly single quantity distribution interval, plans the optimal monthly single quantity distribution interval in the month dimension in advance, which can provide guidance for subsequent stage single distribution (such as daily single distribution), and then refines the stage single distribution constraint condition of the current stage from the monthly single quantity distribution interval, combines the monthly prediction with simulation and stage dynamic adjustment, realizes the all-round optimization from macro to micro, and effectively realizes the consistency between the monthly cost optimization and real-time single distribution. In addition, because the monthly single quantity distribution interval is determined based on various distribution reference information and the upper and lower limits of the cycle discount single quantity, it is more reasonable and forward-looking, and its refinement to the current update stage can combine the fluctuation characteristics of actual orders in different time periods, so that the order distribution of each update stage is more in line with the actual situation, which helps to more accurately control the order distribution process.

[0109] In one specific embodiment, step S121b can determine the stage order allocation constraint condition corresponding to the current update stage of the candidate logistics provider according to the following steps a-b.

[0110] Step a: determining the daily order allocation constraint condition corresponding to the candidate logistics provider according to the monthly order allocation interval corresponding to the candidate logistics provider, wherein the daily order allocation constraint condition is used to represent the distribution interval satisfied by the order quantity allocated to the candidate logistics provider each day.

[0111] Each of the update stages is less than one day.

[0112] Specifically, the daily order allocation constraint condition of the current month can be determined according to the monthly order allocation interval of the current month. Specifically, the monthly order allocation interval can be evenly distributed to each day according to the number of days in the current month to obtain the daily order allocation constraint condition. However, considering the actual fluctuation of orders, the obtained daily order allocation constraint condition can also be adjusted in combination with historical order data to obtain an adjusted daily order allocation constraint condition. For example, if historical data shows that the order quantity of Monday is usually high, the upper limit and lower limit of the daily order allocation constraint condition of Monday can be appropriately increased when determining the daily order allocation constraint condition of Monday.

[0113] In step a, the preliminary daily order allocation constraint condition of the current month can be determined according to the monthly order allocation interval at the start time of each month, and the final daily order allocation constraint condition of the current day can be obtained by adjusting the preliminary daily order allocation constraint condition according to the allocated order data of the current month and the monthly order allocation interval at the start time of each day. In this way, the real-time changes of daily order allocation can be fully considered, and the daily order allocation constraint condition can be more in line with the actual order demand. For example, if the actual order quantity of a certain day is much higher than expected, the upper limit of order allocation of the subsequent days can be reduced in the adjustment of the order allocation constraint condition of the subsequent days to ensure the rationality of the monthly order allocation interval.

[0114] In one specific embodiment, step a can determine the daily order allocation constraint condition corresponding to the candidate logistics provider according to the following steps: predicting the order quantity of the current day; and determining the daily order allocation constraint condition corresponding to the candidate logistics provider according to the order quantity of the current day and the monthly order allocation interval corresponding to the candidate logistics provider.

[0115] Specifically, the order quantity of the current day can be predicted according to at least one of historical order data, attribute information of the current day (including at least one of whether it is a weekday, a holiday, and a promotion day), and real-time order data. For example, the order quantity of the previous day can be predicted as the order quantity of the current day, or the order quantity of a historical date with the same attribute information as the attribute information of the current day in the historical order data can be predicted as the order quantity of the current day.

[0116] In the process of determining the daily order distribution constraint condition of the candidate logistics provider according to the daily order volume and the monthly order volume distribution interval corresponding to the candidate logistics provider, the proportion of the daily order volume in the monthly order volume distribution interval can be calculated, and the daily order distribution constraint condition corresponding to the candidate logistics provider can be determined according to the proportion. For example, if the daily order volume proportion is large, and the candidate logistics provider has a large remaining amount in the monthly order volume distribution interval, the upper limit and the lower limit of the daily order distribution constraint condition of the candidate logistics provider can be increased; if the daily order volume proportion is small, or the remaining amount of the candidate logistics provider in the monthly order volume distribution interval is not large, the upper limit and the lower limit of the daily order distribution constraint condition of the candidate logistics provider can be reduced.

[0117] For example, the monthly order volume distribution interval of a certain candidate logistics provider is [1000, 2000] orders, and there are 30 days in the month. According to the historical data and the daily attribute information, it is predicted that the daily order volume is 200 orders, and the day is in a time period with high order volume. If the daily order volume interval is [1000 ÷ 30 ≈ 33, 2000 ÷ 30 ≈ 67] orders according to the average distribution, considering that the daily order volume is large and the logistics provider has a large remaining amount in the monthly interval, the daily order distribution constraint condition can be adjusted to [50, 100] orders.

[0118] The embodiment determines the daily order distribution constraint condition according to the predicted daily order volume, which can better adapt to the dynamic changes of daily order volume and make the order distribution decision more flexible and accurate.

[0119] Step b: determining the stage order distribution constraint condition corresponding to the candidate logistics provider in the current update stage according to the daily order distribution constraint condition.

[0120] Since each update stage is less than one day, after determining the daily order distribution constraint condition, the daily order distribution constraint condition can be further refined to each update stage, for example, to the order distribution constraint condition of each hour. Specifically, the daily order distribution constraint condition can be proportionally divided into the stage order distribution constraint conditions corresponding to each update stage according to the time proportion of each update stage in a day.

[0121] Alternatively, the stage order distribution constraint condition of the current update stage can also be dynamically adjusted at the starting time of each update stage in combination with the allocated order state information and the daily order distribution constraint condition of the day. For example, if the allocated order progress far exceeds the expectation at the beginning of a certain update stage, and the remaining allocatable order volume of the day is reduced, the order distribution upper limit of the current update stage can be reduced. Through this dynamic adjustment, the order distribution constraint condition of each update stage can be more in line with the actual order distribution situation, further improving the accuracy and flexibility of order distribution.

[0122] The embodiment gradually refines the order allocation constraints in various dimensions from the monthly, daily to the updating stage, so that the order allocation can fully consider the order characteristics and actual situation in different time scales. At the monthly level, based on various allocation reference information and the upper and lower limits of the periodic discount order quantity, a reasonable monthly order quantity allocation interval is determined to provide macro guidance for subsequent order allocation. At the daily level, the monthly order quantity allocation interval is adjusted in combination with historical order data to obtain daily order allocation constraints that are more in line with actual order fluctuations, and the daily allocated order data is dynamically adjusted. At the updating stage level, the daily order allocation constraints are further refined, and the dynamic adjustment is made in combination with the state information of the allocated orders of the day, so that the order allocation constraints of each updating stage can closely match the actual order allocation situation. This multi-dimensional gradual refinement and dynamic adjustment of order allocation can not only effectively achieve consistency between monthly cost optimization and real-time order allocation, but also better meet the upper and lower limits of the periodic discount order quantity of each logistics provider, so that the comprehensive logistics cost is lower.

[0123] In one specific embodiment, step b can determine the stage order allocation constraints corresponding to the current updating stage of the candidate logistics provider according to the following steps b1-b2.

[0124] Step b1: For the first updating stage of the day, the stage order allocation constraints corresponding to the first updating stage are determined according to the order allocation data of the previous day and the daily order allocation constraints.

[0125] Specifically, the daily order allocation constraints can be divided according to the time proportion of each updating stage to obtain preliminary order allocation constraints for each updating stage, and then the preliminary order allocation constraints for the first updating stage of the day are adjusted according to the stage order allocation constraints of the first updating stage of the previous day, so that the order allocation constraints of the first updating stage of the day are more in line with the actual order situation. For example, if the order allocation quantity of the first updating stage of the previous day is much higher than expected, and the order trend shows that the order quantity may continue to be high, then the upper limit of the order allocation constraints of the first updating stage of the day can be increased. If the order quantity of the first updating stage of the previous day is low, and there are no fluctuations such as festivals or promotions on the day, then the lower limit of the order allocation constraints of the first updating stage of the day can be reduced.

[0126] In the embodiment, since the order quantity of the current first updating stage is unknown, the order allocation constraints are determined by referring to the order allocation data of the previous day. By comparing the order situation of the first updating stage of the previous day, a preliminary prediction of the order trend of the first updating stage of the day can be made, so that the preliminary order allocation constraints can be adjusted to avoid the problem of disconnection with the actual order situation caused by directly dividing the daily order allocation constraints according to the time proportion.

[0127] Step b2: For each update stage of the day other than the first update stage, obtain the number of orders generated that day, and update the stage order allocation constraints corresponding to the target update stage based on the number of orders generated and the order allocation constraints for the day.

[0128] Specifically, after obtaining the number of orders generated for the day, the difference between the number of orders allocated to candidate logistics providers up to the start of the current update phase and the lower and upper limits of the daily order allocation constraints can be calculated. Based on this difference, the corresponding stage order allocation constraints for the update phase can be updated. For example, if the number of generated orders is close to or has reached the lower limit of the daily order allocation constraints, but there is still significant room to reach the upper limit, and real-time order data indicates a continued growth trend in orders, then the upper limit of the order allocation constraints for the current update phase can be appropriately increased to fully utilize the daily allocation quota and improve logistics efficiency. If the number of generated orders is close to or has reached the upper limit of the daily order allocation constraints, to ensure that the daily allocation quota limit is not exceeded, the upper limit of the order allocation constraints for the current update phase should be decreased, and the lower limit may even be appropriately lowered.

[0129] This embodiment targets update stages other than the first update stage of the day. Based on the generated order volume and the daily order allocation constraints, it dynamically updates the stage order allocation constraints, which can further improve the accuracy and flexibility of order allocation. This ensures that order allocation can not only meet the logistics provider's discount order volume requirements, but also adapt to real-time order changes, thereby optimizing logistics costs and improving the efficiency of order allocation.

[0130] Example 2

[0131] The second embodiment of this application also provides a logistics order splitting device corresponding to the logistics order splitting method embodiment provided in the first embodiment. Since the device embodiment is basically similar to the method embodiment, it is described simply. For details of the relevant technical features and their effects, please refer to the corresponding description of the logistics order splitting method embodiment provided above. Figure 3 As shown, the logistics order splitting device provided in this embodiment includes:

[0132] The acquisition unit 210 is used to acquire the unit logistics cost of each candidate logistics provider;

[0133] The update unit 220 is used to update the violation constraint cost corresponding to each of the candidate logistics providers when the preset update conditions are met. The violation constraint cost includes a lower limit violation constraint cost and an upper limit violation constraint cost. The lower limit violation constraint cost is used to represent the logistics cost increased when the order volume in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider. The upper limit violation constraint cost is used to represent the logistics cost increased when the order volume in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider.

[0134] The determination unit 230 is configured to determine a latest constraint violation cost corresponding to the candidate logistics provider at a current time, and correct a unit logistics cost of the candidate logistics provider according to the latest constraint violation cost, to obtain a corrected unit cost of assigning the to-be-assigned order to the candidate logistics provider.

[0135] The selection unit 240 is configured to select a target logistics provider with the lowest corrected unit cost from the candidate logistics providers, and determine a logistics provider to which the to-be-assigned order is assigned based on the target logistics provider.

[0136] Embodiment Three

[0137] The third embodiment of the present application also provides a logistics order distribution system corresponding to the logistics order distribution method provided in the first embodiment. Since the device embodiment is basically similar to the method embodiment, the description is relatively simple, and the details of the related technical features and the effects achieved can be referred to the corresponding description of the logistics order distribution method embodiment provided above. As shown in the figure, the logistics order distribution system provided in the embodiment includes: Figure 4

[0138] The stage dynamic adjustment module 310 is configured to update a constraint violation cost corresponding to each candidate logistics provider when a preset update condition is met, the constraint violation cost including a lower limit constraint violation cost and an upper limit constraint violation cost, the lower limit constraint violation cost being used to represent an increased logistics cost when an order quantity in a corresponding period is lower than a period discount lower limit of the candidate logistics provider, and the upper limit constraint violation cost being used to represent an increased logistics cost when the order quantity in the corresponding period is higher than a period discount upper limit of the candidate logistics provider.

[0139] The real-time order distribution execution module 320 is configured to obtain a unit logistics cost of each candidate logistics provider, determine a latest constraint violation cost corresponding to the candidate logistics provider at a current time from the stage dynamic adjustment module, and correct the unit logistics cost of the candidate logistics provider according to the latest constraint violation cost, to obtain a corrected unit cost of assigning the to-be-assigned order to the candidate logistics provider; select a target logistics provider with the lowest corrected unit cost from the candidate logistics providers, and determine a logistics provider to which the to-be-assigned order is assigned based on the target logistics provider.

[0140] Optionally, the stage dynamic adjustment module is specifically configured to determine a stage order distribution constraint condition corresponding to the candidate logistics provider in a current update stage according to a lower limit and an upper limit of a period discount order quantity of the candidate logistics provider, the stage order distribution constraint condition being used to represent an assignment interval satisfied by an order quantity assigned to the candidate logistics provider in the current update stage; and determine a constraint violation cost of the corresponding candidate logistics provider in the current update stage according to the stage order distribution constraint condition.

[0141] ​Optionally, the logistics order distribution system can further comprise a monthly prediction module 330 configured to determine a monthly order distribution interval of the candidate logistics provider according to a lower limit and an upper limit of the periodic discount order quantity corresponding to the candidate logistics provider, wherein each update stage of the constraint violation cost is less than one month.

[0142] The stage dynamic adjustment module is specifically configured to determine the stage order distribution constraint condition of the candidate logistics provider in the current update stage based on the monthly order distribution interval of the candidate logistics provider predicted by the monthly prediction module.

[0143] Optionally, the logistics order distribution system can further comprise a daily order distribution adjustment module 340 configured to determine a daily order distribution constraint condition of the candidate logistics provider according to the monthly order distribution interval of the candidate logistics provider, wherein the daily order distribution constraint condition is used to represent an order distribution interval satisfied by an order quantity allocated to the candidate logistics provider per day, and each update stage is less than one day.

[0144] The stage dynamic adjustment module is specifically configured to determine the stage order distribution constraint condition of the candidate logistics provider in the current update stage according to the daily order distribution constraint condition.

[0145] Optionally, the logistics order distribution system can further comprise a daily initialization optimization module 350 configured to determine the stage order distribution constraint condition of the first update stage of the day according to the order distribution data of the previous day and the daily order distribution constraint condition.

[0146] The stage dynamic adjustment module is specifically configured to obtain an order quantity generated on the day for the update stage other than the first update stage of the day, and update the stage order distribution constraint condition of the update stage according to the order quantity generated on the day and the daily order distribution constraint condition.

[0147] Optionally, the logistics order distribution system can further comprise a database 360 configured to store historical order distribution data, update the stored historical order distribution data according to the order distribution information obtained by the real-time order distribution execution module 320, and provide the stored historical order distribution data to other modules for order distribution calculation.

[0148] Embodiment Four

[0149] The fourth embodiment of the present application further provides an electronic device embodiment corresponding to the logistics order distribution method provided by the first embodiment. The following description of the electronic device embodiment is merely illustrative. The electronic device embodiment is as follows:

[0150] Please refer to Figure 5 The above electronic device is understood Figure 5The electronic device provided in the embodiment is a schematic diagram of an electronic device. The electronic device provided in the embodiment comprises a processor 1001, a memory 1002, a communication bus 1003, and a communication interface 1004;

[0151] The memory 1002 is configured to store computer instructions for data processing. When the computer instructions are read and executed by the processor 1001, the following steps are performed:

[0152] Obtain the unit logistics cost of each candidate logistics provider;

[0153] When a preset update condition is met, update the constraint violation cost corresponding to each candidate logistics provider, wherein the constraint violation cost comprises a lower limit constraint violation cost and an upper limit constraint violation cost, the lower limit constraint violation cost is used to represent the increased logistics cost when the order quantity in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider, and the upper limit constraint violation cost is used to represent the increased logistics cost when the order quantity in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider;

[0154] Determine the latest constraint violation cost corresponding to the candidate logistics provider at the current time, and correct the unit logistics cost of the candidate logistics provider according to the latest constraint violation cost, to obtain a corrected unit cost of assigning the to-be-assigned order to the candidate logistics provider;

[0155] Select a target logistics provider with the lowest corrected unit cost from the candidate logistics providers, and determine the logistics provider to which the to-be-assigned order is assigned based on the target logistics provider.

[0156] The fifth embodiment of the present application also provides a computer readable storage medium for implementing the method of the first embodiment. The computer readable storage medium embodiment provided in the present application is described relatively simply, and the related parts refer to the corresponding description of the above-mentioned method embodiment. The following described embodiments are only illustrative.

[0157] The computer readable storage medium provided in the embodiment stores computer instructions, and the computer instructions are executed by a processor to implement the following steps:

[0158] Obtain the unit logistics cost of each candidate logistics provider;

[0159] When a preset update condition is met, update the constraint violation cost corresponding to each candidate logistics provider, wherein the constraint violation cost comprises a lower limit constraint violation cost and an upper limit constraint violation cost, the lower limit constraint violation cost is used to represent the increased logistics cost when the order quantity in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider, and the upper limit constraint violation cost is used to represent the increased logistics cost when the order quantity in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider;

[0160] determine a latest constraint violation cost corresponding to the candidate logistics provider at the current time, and correct a unit logistics cost of the candidate logistics provider according to the latest constraint violation cost, to obtain a corrected unit cost of assigning the to-be-assigned order to the candidate logistics provider;

[0161] select a target logistics provider with the lowest corrected unit cost from the candidate logistics providers, and determine a logistics provider to which the to-be-assigned order is assigned based on the target logistics provider.

[0162] In one typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0163] The memory can include non-persistent memory in the computer readable medium, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer readable media.

[0164] 1. Computer readable media includes permanent and non-permanent, removable and non-removable media can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape disk storage or other magnetic storage device, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. According to the definition in this application, computer readable media does not include non-transitory computer readable media (transitory media), such as modulated data signals and carriers.

[0165] 2. Those skilled in the art should understand that the embodiments of the present application can provide methods, systems or computer program products. Therefore, the embodiments of the present application can adopt a completely hardware embodiment, a completely software embodiment or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0166] 3. This application embodiment may involve the use of user data. In practical applications, user-specific personal data may be used within the scope permitted by applicable laws and regulations of the country in which the application is located (e.g., with the user's explicit consent and effective notification to the user, etc.). Furthermore, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. The collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0167] Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of this application. Therefore, the scope of protection of this application should be determined by the scope defined in the claims of this application.

Claims

1. A logistics order splitting method, characterized in that, The method includes: Obtain the unit logistics cost for each candidate logistics provider; When the preset update conditions are met, the violation constraint cost corresponding to each candidate logistics provider is updated. The violation constraint cost includes a lower limit violation constraint cost and an upper limit violation constraint cost. The lower limit violation constraint cost is used to represent the logistics cost increased when the order volume in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider. The upper limit violation constraint cost is used to represent the logistics cost increased when the order volume in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider. Determine the latest constraint violation cost corresponding to the candidate logistics provider at the current moment, and adjust the unit logistics cost of the candidate logistics provider based on the latest constraint violation cost to obtain the adjusted unit cost for allocating the order to be assigned to the candidate logistics provider; Select the target logistics provider with the lowest modified unit cost from among the candidate logistics providers, and determine the logistics provider to be assigned to the order based on the target logistics provider.

2. The logistics order splitting method according to claim 1, characterized in that, The update of the violation cost for each of the candidate logistics providers includes: Based on the lower and upper limits of the periodic discount order volume of the candidate logistics provider, the phase order allocation constraint conditions corresponding to the candidate logistics provider in the current update phase are determined. The phase order allocation constraint conditions are used to represent the allocation range satisfied by the order volume allocated to the candidate logistics provider in the current update phase. The cost of violating constraints for the corresponding candidate logistics provider in the current update phase is determined according to the phased order allocation constraints.

3. The logistics order splitting method according to claim 2, characterized in that, The step of determining the phase-based order allocation constraints for the candidate logistics provider in the current update phase based on the lower and upper limits of the candidate logistics provider's periodic discount order volume includes: The monthly order volume allocation range of the candidate logistics provider is determined based on the lower limit and upper limit of the periodic discount order volume corresponding to the candidate logistics provider, and each update stage of the violation constraint cost is less than one month. Based on the monthly order volume allocation range corresponding to the candidate logistics provider, the phase order allocation constraints corresponding to the candidate logistics provider in the current update phase are determined.

4. The logistics order splitting method according to claim 3, characterized in that, The step of determining the monthly order volume allocation range for the candidate logistics provider based on the lower and upper limits of the corresponding periodic discount order volume includes: Obtain allocation reference information, which includes at least one of historical order allocation data, future order volume prediction data, and order targets; Based on the allocation reference information and the lower and upper limits of the candidate logistics provider's periodic discount order volume, the monthly order volume allocation range of the candidate logistics provider is determined.

5. The logistics order splitting method according to claim 3, characterized in that, The step of determining the phase-based order allocation constraints for the candidate logistics provider in the current update phase, based on the monthly order volume allocation range corresponding to the candidate logistics provider, includes: Based on the monthly order volume allocation range corresponding to the candidate logistics provider, the daily order allocation constraint condition corresponding to the candidate logistics provider is determined. The daily order allocation constraint condition is used to represent the allocation range satisfied by the order volume allocated to the candidate logistics provider each day, and each update stage is less than one day. Based on the daily order allocation constraints, determine the stage order allocation constraints corresponding to the candidate logistics provider in the current update stage.

6. The logistics order splitting method according to claim 5, characterized in that, The step of determining the daily order allocation constraints for the candidate logistics providers based on their monthly order volume allocation intervals includes: Forecast the daily order volume; Based on the daily order volume and the monthly order volume allocation range corresponding to the candidate logistics provider, determine the daily order allocation constraints corresponding to the candidate logistics provider.

7. The logistics order splitting method according to claim 6, characterized in that, The step of determining the stage-based order allocation constraints for the candidate logistics provider in the current update stage based on the daily order allocation constraints includes: For the first update phase of the day, the phase order allocation constraints corresponding to the first update phase are determined based on the order allocation data of the previous day and the daily order allocation constraints. For each update stage of the day other than the first update stage, obtain the number of orders generated that day, and update the stage order allocation constraints corresponding to the target update stage based on the number of orders generated and the order allocation constraints for the day.

8. The logistics order splitting method according to claim 1, characterized in that, The lower limit violation cost is represented by the lower limit dual value, and the upper limit violation cost is represented by the upper limit dual value. The lower limit dual value is the dual value when the order volume in the corresponding period is greater than the lower limit of the discount of the candidate logistics provider, and the upper limit dual value is the dual value when the order volume in the corresponding period is less than the upper limit of the discount of the candidate logistics provider.

9. The logistics order splitting method according to claim 1, characterized in that, The step of determining the logistics provider to be assigned to the order based on the target logistics provider includes: When the target logistics provider's transportation volume in the current period does not reach the preset threshold, the target logistics provider will be identified as the logistics provider assigned to the order to be assigned. When the target logistics provider's transportation volume reaches a preset threshold in the current period, a secondary target logistics provider with a higher unit cost than the target logistics provider is selected from among the candidate logistics providers, and the logistics provider to be assigned to the order is determined based on the secondary target logistics provider.

10. The logistics order splitting method according to any one of claims 1 to 9, characterized in that, The preset update conditions include at least one of the following: reaching a preset time interval point, generating a new order to be assigned, completing the splitting of the order to be assigned, and the number of completed splitting orders reaching a preset quantity interval, wherein the preset time interval is any interval between 30 minutes and 2 hours.

11. The logistics order splitting method according to claim 1, characterized in that, The step of adjusting the unit logistics cost of the candidate logistics provider based on the latest constraint violation cost to obtain the adjusted unit cost for allocating orders to the candidate logistics provider includes: The sum of the unit logistics cost and marginal cost of the candidate logistics provider is determined as the modified unit cost for allocating the orders to be assigned to the candidate logistics provider. The marginal cost is positively correlated with the upper limit constraint violation cost and negatively correlated with the lower limit constraint violation cost.

12. A logistics order splitting device, characterized in that, The device includes: The acquisition unit is used to acquire the unit logistics cost of each candidate logistics provider; The update unit is used to update the violation cost corresponding to each of the candidate logistics providers when the preset update conditions are met. The violation cost includes a lower limit violation cost and an upper limit violation cost. The lower limit violation cost is used to represent the logistics cost increased when the order volume in the corresponding period is lower than the lower limit of the period discount of the candidate logistics provider. The upper limit violation cost is used to represent the logistics cost increased when the order volume in the corresponding period is higher than the upper limit of the period discount of the candidate logistics provider. The determining unit is used to determine the latest constraint violation cost corresponding to the candidate logistics provider at the current time, and to correct the unit logistics cost of the candidate logistics provider based on the latest constraint violation cost, so as to obtain the corrected unit cost for allocating the order to be assigned to the candidate logistics provider. The selection unit is used to select the target logistics provider with the lowest modified unit cost from among the candidate logistics providers, and to determine the logistics provider to be assigned to the order to be assigned based on the target logistics provider.

13. An electronic device, characterized in that, include: Processor, memory, and computer program instructions stored in said memory and executable on the processor; When the processor executes the computer program instructions, it implements the method as described in any one of claims 1-11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-11.

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