CN113421140A

CN113421140A - Order processing method, device and system and electronic equipment

Info

Publication number: CN113421140A
Application number: CN202010393203.7A
Authority: CN
Inventors: 汪洋; 王晓晴; 王桐; 王威; 邓玉明; 赵明勇; 漆星星; 曹雷
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2020-05-11
Filing date: 2020-05-11
Publication date: 2021-09-21

Abstract

The embodiment of the invention provides an order processing method, an order processing device, an order processing system and electronic equipment, wherein the order processing method comprises the following steps: acquiring a first order quantity in a current order pool, a first order combining probability of at least one order and first logistics capacity; determining a first order placing quantity which needs to perform order placing and sending processing to the logistics on the current order pool according to the first order combining probability and the first logistics capacity; and selecting an order from the order pool according to the first order quantity, and placing the order to the logistics system. The embodiment of the invention dynamically determines the number of the orders issued to the downstream logistics at present based on the order combination probability of the orders in the order pool and the downstream logistics capacity condition, thereby maintaining the balance between the order combination waiting of the orders in the order pool and the downstream logistics capacity matching and improving the utilization rate of logistics resources.

Description

Order processing method, device and system and electronic equipment

Technical Field

The application relates to an order processing method, an order processing device, an order processing system and electronic equipment, and belongs to the technical field of computers.

Background

In the e-commerce field, when a user purchases online shopping, a plurality of commodities are often purchased in a short time, so that a plurality of orders are sequentially generated and distributed to the same receiving address. In this case, when the logistics operation is performed, the plurality of orders are consolidated and shipped, and the in-warehouse operation cost and the delivery cost can be reduced.

For such a situation, in the prior art, the generated user order is not immediately placed to a logistics department such as a warehouse, but the order stays in the order pool for a predetermined time to wait for an order that may be combined, and then the order is placed to the logistics.

However, in the scheme in the prior art, the time for the order to stay in the order pool is fixed, and the order cannot be changed after entering the order pool, so that the order in the order pool cannot be reasonably allocated, the order pool is congested, the order placement distribution efficiency is low, and the like.

Disclosure of Invention

The embodiment of the invention provides an order processing method, an order processing device, an order processing system and electronic equipment, and aims to improve the utilization efficiency of logistics resources.

In order to achieve the above object, an embodiment of the present invention provides an order processing method, including:

acquiring a first order quantity in a current order pool, a first order combining probability of at least one order and first logistics capacity;

determining a first order placing quantity which needs to perform order placing and sending processing to the logistics for the current order pool according to the first order combining probability and the first logistics capacity;

and selecting an order from the order pool according to the first order placing quantity, and placing the order to a logistics system.

The embodiment of the invention also provides an order processing method, which comprises the following steps:

grouping orders according to their category relating to products and/or delivery time requirements;

for each order group generated after grouping, the following processing is respectively executed:

receiving a list combination inquiry message aiming at an existing order from a server;

and returning a list feedback message to the server, wherein the list feedback message comprises one or more items of information on whether a list exists, a commodity to be listed and list waiting time.

sending a bill combination inquiry message to a user side;

receiving an order feedback message from a user side, and determining a first order combining probability of the user's order in an order pool according to the order feedback message, wherein the order feedback message comprises one or more items of information on whether an order exists or not, a commodity to be combined and order combining waiting time.

receiving a logistics situation inquiry message from a server;

determining the number of available orders and/or the order logistics processing waiting time according to the current logistics capacity and the number of unprocessed orders;

and feeding back a logistics state feedback message containing the number of available orders and/or the order logistics processing waiting time to the server.

sending a logistics condition inquiry message to a logistics system;

receiving a logistics condition feedback message containing the number of available orders and/or the order logistics processing waiting time from the logistics system;

determining a first logistics capacity of the logistics system according to the number of the order-receiving and/or the order logistics processing waiting time

An embodiment of the present invention further provides an order processing apparatus, including:

the data acquisition module is used for acquiring a first order quantity in the current order pool, a first order combining probability of at least one order and first logistics capacity;

the order placing quantity determining module is used for determining a first order placing quantity which needs to perform order placing processing to the logistics on the current order pool according to the first order combining probability and the first logistics capacity;

and the order placing processing module is used for selecting an order from the order pool according to the first order placing quantity and executing order placing processing to a logistics system.

An embodiment of the present invention further provides an order processing system, including:

the order combining probability estimation module is used for receiving orders generated by the e-commerce trading platform, storing the orders into an order pool, periodically carrying out order combining probability estimation on the orders in the order pool, generating a first order combining probability of at least one order and sending the first order combining probability to the order placing quantity decision module;

the order quantity decision module is used for respectively acquiring a predicted first incoming order quantity, a predicted first logistics capacity and a predicted first order quantity in an order pool from an e-commerce trading platform, a logistics system and the order pool, determining a first order quantity which needs to perform order sending processing to logistics for the current order pool according to the first incoming order quantity, the first logistics capacity, the predicted first order quantity in the order pool and the predicted first order quantity in the order pool, determining the first order quantity in the order pool according to the first incoming order quantity, the predicted first logistics capacity, the predicted first order quantity in the order pool and the predicted first order probability of each order, and sending the first order quantity to the order pool;

the order pool is used for caching the orders, ranking the orders and the first order taking amount according to the first order combining probability of each order, selecting the orders and sending the orders to the order taking execution module;

and the order placing execution module is used for carrying out order combination processing on the received orders and sending the orders after the orders are combined to the logistics system.

An embodiment of the present invention further provides an electronic device, including:

a memory for storing a program;

and the processor is used for operating the program stored in the memory so as to execute the order processing method.

The embodiment of the invention dynamically determines the number of orders issued to the downstream logistics at present based on the order combination probability of the orders in the order pool and the capacity condition of the downstream logistics, thereby better maintaining the balance between the order combination waiting of the orders in the order pool and the capacity matching of the downstream logistics, realizing the maximization of the overall profit and improving the utilization rate of logistics resources.

The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.

Drawings

FIG. 1 is a schematic diagram of an application framework of an order processing system according to an embodiment of the invention;

FIG. 2 is a flowchart illustrating an order processing method according to an embodiment of the invention;

FIG. 3 is a schematic structural diagram of an order processing apparatus according to an embodiment of the present invention;

FIG. 4 is a schematic structural diagram of an order processing system according to an embodiment of the present invention;

FIG. 5 is a second flowchart illustrating an order processing method according to an embodiment of the invention;

FIG. 6 is a third flowchart illustrating an order processing method according to a third embodiment of the present invention;

FIG. 7 is a fourth flowchart illustrating an order processing method according to an embodiment of the present invention;

FIG. 8 is a fifth flowchart illustrating an order processing method according to an embodiment of the present invention;

fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

The technical scheme of the embodiment of the invention can be used for determining a reasonable order number for the order pool in the E-commerce field, so that orders with the order number are taken out from the current order pool to be issued to downstream logistics, and the orders left in the order pool continue to wait for the possible follow-up order combination opportunities. The utilization efficiency of logistics resources is improved through the mechanism. Specifically, the embodiment of the invention determines the reasonable lower singular number by calculating the profit formed by the difference between the contract cost and the logistics capacity loss.

From the perspective of order saving cost, if the probability that the orders in the order pool are multiple on the whole is high, more orders should be kept in the order pool, and more orders are likely to occur, so that the logistics cost is saved. The above-mentioned order-closing probability may be determined according to one or more of the historical consumption behavior of the user, the order structure of the user, and the sales promotion activity related to the order, for example, it is customary in the historical consumption behavior that in each online shopping, the purchase is continuously performed at short intervals to generate a plurality of individual orders, and for example, some products have certain collocation, and after the user purchases a mobile phone, it is likely to purchase a mobile phone shell, so that two orders which can be combined are generated, and for example, during the sales promotion period, the possibility that the user continuously generates a plurality of orders is also high.

On the other hand, from the downstream logistics capacity, if the downstream logistics has idle conditions, the logistics capacity is wasted, more orders should be placed from the order pool to meet the logistics capacity, and conversely, if the downstream logistics has saturated conditions, in this case, more orders are placed, only the saturation of the downstream logistics can be increased, in this case, the orders are not kept in the order pool for more contract orders, so that the order placing quantity is matched with the logistics capacity as much as possible for the downstream logistics capacity.

For the former order-taking savings cost and the loss of the capacity of the stream, if the capacity of the downstream stream is basically stable, the two factors are mainly determined by the order-taking probability of the order and the order-placing number of the order placed to the downstream stream. The embodiment of the invention determines a reasonable ordering number by establishing an objective function based on the principle that the difference between the order saving cost and the logistics capacity loss is the generated income maximization, thereby executing ordering processing on the order pool. In the process, the order pool plays a role in waiting for order combination and directly buffering downstream logistics supply, so that the utilization rate of logistics resources is effectively improved.

In addition, after the reasonable order placing number is determined, all orders in the order pool can be ranked according to the order combining probability, the order with the lower order combining probability is selected, and the order placing processing is executed.

According to the technical scheme of the embodiment of the invention, the number of orders issued to the downstream logistics at present is dynamically determined on the basis of the order combination probability of the orders in the order pool and the downstream logistics capacity condition, so that the balance between order combination waiting of the orders in the order pool and downstream logistics capacity matching is better maintained, the maximization of the overall benefit is realized, and the utilization rate of logistics resources is improved.

The reasonable orders can be processed through an order quantity decision model, and the input of the order quantity decision model is the order quantity in the current order pool, the predicted incoming order quantity in the future time period, the order probability of each order in the order pool and the downstream operation capacity. The model determines the order number of orders needing to be issued to logistics by realizing the mode of maximizing the overall income of the following objective function and combining constraint conditions, thereby triggering an order pool to perform order issuing processing.

Objective function

As a specific example, the following single-quantity decision model of the embodiment of the present invention introduces an objective function for calculating the total Gain (Gain), and the expression of the objective function is as follows:

in the above objective function, the first part corresponds to the aggregate savings cost and the second part corresponds to the loss of the logistics capacity. In the technical scheme of the embodiment of the invention, parameter statistics is carried out every unit time period t. The objective function not only calculates the aggregate saving cost and the logistics capacity loss in the current time period, but also predicts the aggregate saving cost and the logistics capacity loss in the future time T and carries out comprehensive evaluation.

In the above objective function, T is the number of the current unit period, and T is the number of future unit periods after the current unit period. In the first part, p is the average order probability of each order in the current order pool, S is the order quantity in the order pool_τThe order quantity in the order pool in the time period is represented by c, the order saving cost brought by the order combination of the unit order is represented by c, and the first part in the objective function can carry out accumulation summation on the order saving cost of T +1 unit time periods. In the second section, w is the logistics capacity loss per unit order, ε⁺For making a single-quantity insufficient material flowThe order quantity of capacity, i.e. the amount of orders, epsilon, which cause idle logistics resources^-In order to place orders in amounts that exceed the orders for the logistics capacity, i.e. the orders that result in oversaturation of the logistics resources, and, correspondingly,

and

the second part of the objective function is to sum the demand amount of the insufficient logistics capacity and the demand amount of the order amount exceeding the logistics capacity in the time period, wherein the demand amount of the logistics capacity in the T +1 unit time period is less than the demand amount of the order amount exceeding the logistics capacity in the time period,

and

are all positive numbers.

On the basis of the above objective function, there is a constraint condition to finally determine a reasonable lower singular number.

One of the constraints is: variable relation of order quantity

Order quantity in pool S for time period t +1_t+1Amount of orders in pool with time period t S_tThe following relationship is satisfied:

S_t+1＝S_t+O_t+I_tformula (2)

Wherein, O_tThe amount of the downstream material flow in the time period t is the amount which needs to be finally determined by the objective function in the technical scheme of the embodiment of the invention. The order quantity corresponding to a plurality of time periods t is determined through iterative processing, and in the embodiment of the invention, the order quantity in the current time period is only required to be selected to execute order placing. When the next time period comes, the next single quantity decision model is used again to determine the next single quantity again. I is_tFor a predicted amount of incoming money for a time period t, the predicted amount of incoming money may be advanced based on factors such as historical transaction data and whether a promotional program is presentAnd (6) line prediction. In summary, the constraint determines the respective S of the first part of the objective function_τ。

The second constraint condition is as follows: the lower unit amount exceeds the amount of the produced energy

The constraint condition actually gives

And

and

corresponding to the lower single amount O in the t period_tA positive difference from the current downstream capacity indicates that the next sheet is too large, and, at this point,

is 0, and

equal to the difference, otherwise, when the difference is negative, the next unit quantity does not meet the current downstream logistics capacity, the logistics capacity is still idle, at this time,

is 0, and

equal to the difference.

The third constraint condition is as follows: time to order

The order interception time may be a time point or a time length. To prevent orders from being in the order pool too long, a pick-up time, i.e., the maximum time an order is in the order pool, may be set and when this time is exceeded, the order is forced. The order taking time can also be set for the whole order pool, and the orders in the order pool are forcibly placed after the order taking time of the orders is reached. For example, the current order must be placed every day 6 pm, etc.

A fourth constraint condition; order pool capacity

Generally, the order pool capacity is limited, so the order quantity S in the order pool is limited by the order pool capacity and cannot exceed the order pool capacity.

The objective function and its operating principle in the embodiment of the present invention are described above. And based on the objective function and the constraint conditions, estimating the order saving cost and the logistics capacity loss of T time periods in the future by using the order combining probability of each order in the current order pool and the order placing amount of the downstream logistics to be determined, calculating the overall profit of the objective function according to the order combining cost and the logistics capacity loss, determining the order placing amount which can maximize the overall profit through repeated iteration, and then selecting the orders with lower order combining probability and the number corresponding to the order placing amount from the order pool to place the orders.

The above-described objective function calculation and order placement amount determination processing may be performed once every the above-described unit time period t, that is, the order placement processing may be performed once every the above-described unit time period t.

Order grouping process

In terms of logistics, orders may be divided into categories, for example, some orders may require delivery on the same or the next day, and some orders may require delivery within a week. There may be differences in the strategies for determining the probability of a combination and the amount of orders placed based on the order. Therefore, the embodiment of the present invention proposes that the orders may be grouped according to the types of the orders, and then the objective function is executed for each group of orders, so as to finally determine the order placing amount corresponding to the group of orders.

In addition, the following describes an order processing overall framework according to an embodiment of the present invention, as shown in fig. 1, which is an application framework schematic diagram of an order processing system according to an embodiment of the present invention, and the overall application environment relates to an e-commerce trading platform, a logistics system, and an order processing system. The e-commerce trading platform is used for providing online shopping service for users, and the users can generate orders after selecting commodities on the e-commerce trading platform and paying successfully. These newly generated orders arrive at the order processing system of embodiments of the present invention. When a new order comes, the order processing system order combination probability estimation model evaluates the order combination probability of the new order, generates an order combination probability for each order and provides the order combination probability for the order placing decision model. And newly generated orders are also entered into the order pool. In addition, the order probability estimation model can also periodically re-evaluate the order probability of each order in the order pool so as to provide support for the order probability data for the order quantity decision model.

The order quantity decision model is a core part of an order processing system and is used for making order quantity decisions through four aspects of data input. The order probability of each order is from the order probability estimation model, the order quantity in the future time period can be predicted from the E-commerce trading platform, specifically, the prediction can be carried out according to factors such as historical data, whether promotion activities exist currently and the like, the data in the aspect of logistics capacity can be from the logistics system, and the order pool can provide relevant data of the order quantity in the current order pool. The order quantity decision model finally outputs the order quantity which needs to be placed to the logistics system at present and provides the order quantity to the order pool.

And the order pool ranks the orders in the order pool according to the order combining probability, and selects the orders to be issued corresponding to the order placing quantity according to the ranking sequence from low to high in order combining probability after receiving the order placing quantity output by the order placing quantity decision model, and provides the orders to be issued to the order placing execution module to execute order placing processing.

The order placing execution module performs order combining processing on orders meeting order combining conditions in the orders to be placed, for example, the orders are combined with a plurality of orders of a user, and then the orders subjected to the order combining processing are provided for the logistics system to execute logistics operation.

The technical solutions of the embodiments of the present invention are further described below by some specific embodiments.

Example one

As shown in fig. 2, which is a schematic flow chart of an order processing method according to an embodiment of the present invention, the method may be applied to an e-commerce platform or a logistics system, and the method specifically may include:

s101: a first order quantity in a current order pool, a first order combining probability of at least one order and a first logistics capacity are obtained. In the embodiment of the invention, the order pool is used as a buffer storage module of the order, after the e-commerce platform generates the order, the order is firstly buffered and stored in the order pool for a period of time and then placed to the downstream logistics system, and the aim of waiting for other orders of the same user is to facilitate the order combination processing, so that the utilization rate of logistics resources is effectively improved. In an embodiment of the present invention, dispatching an order to a downstream logistics system is referred to as placing an order. The first order quantity refers to the number of orders in the order pool before orders are placed to the downstream logistics system, the order combining probability refers to the probability that a user corresponding to an order generates the order again for the order, and the logistics generation refers to the number of orders which can be processed by the downstream logistics system.

The first order probability may be evaluated by the order probability estimation model described above, wherein the evaluation elements may include the user's historical consumption behavior, the user's order structure, the promotional activities involved in the order, etc., and the first order probability evaluation may be performed every predetermined period of time, for example, every 5 minutes to evaluate the order probability for the orders in the order pool. Since the order quantity changes rapidly, if all orders in the order pool are evaluated once every new order enters the order pool, certain resources are wasted, and therefore, better processing efficiency can be obtained by evaluating once every other time. In addition, the order structure of the user can be better obtained through centralized evaluation of the orders, so that more accurate order combination probability can be evaluated. The first logistics capacity can be from a mechanism for performing logistics processing, such as the logistics system performing comprehensive logistics control in the previous example, or can be a warehouse system or a distribution and transportation system.

S102: and determining a first order placing quantity which needs to perform order placing and sending processing to the logistics on the current order pool according to the first order combining probability and the first logistics capacity. Specifically, in this step, a first order quantity required to perform the order placing to the logistics for the current order pool is determined through a predetermined objective function, and the objective function determines the overall profit according to the first order saving cost of the order pool and the first logistics capacity loss. Wherein the first order cost savings is determined based on a first order quantity in the order pool and a first order probability of the at least one order, and the first logistics capacity loss is determined based on a degree of matching of the first logistics capacity to the first order quantity.

In the embodiment of the present invention, the first demographics amount is determined with the objective of optimizing the overall profit, that is, a value of a certain first demographics amount is determined, so that a better overall profit is obtained. In the actual processing, the order quantity in the case where the overall profit is maximized may be determined as the first order quantity of the above-described order placing process to the physical distribution with the objective of the overall profit maximization. For a specific calculation processing process, the objective function can be used to calculate the overall profit corresponding to a plurality of different order placing quantities, and the order placing quantity with better overall profit is selected to execute the order placing. The selection of the order quantity can be calculated based on a first order quantity executed in the previous time as an initial trial value, then the order quantity is increased or decreased on the basis of the initial value, and finally the corresponding order quantity under the condition that the overall profit is better or the maximum is found as the finally determined first order quantity.

In the objective function, two factors, namely the first order saving cost and the logistics capacity loss, need to be calculated respectively, and the overall profit is evaluated by the two factors, and the detailed formula example can refer to the above formula (1). The order-merging cost saving represents the logistics cost saved by merging a plurality of orders. The logistics capacity loss represents the loss caused by the mismatching of the order quantity placed to the logistics system and the capacity of the logistics system, and can be the order overstock caused by the fact that the capacity is not met or the capacity is insufficient. The more cost savings the aggregate is, the less the loss of logistics capacity, and the greater the overall revenue.

In detail, on the one hand, the more orders consolidated performed upstream, the more logistics costs can be saved, which is hoped to be better the longer an order can be left in the order pool, because the greater the probability of getting a bond; on the other hand, the downstream logistics system does not want to have capacity idle condition, because if the capacity is idle, it means that the capacity is wasted, the yield is reduced, and it is also not wanted to issue orders to the logistics system in excess of the sustainable capacity, because if orders exceeding the capacity occur, the orders must be overstocked in the logistics system, rather than being overstocked in the downstream logistics system, it is placed in the order pool to wait for the order-closing process. Combining the above two factors, the objective function of the embodiment of the present invention is aimed to wait for the balance between the order and the downstream logistics capacity in the order pool, and the closer to the balance state, the greater the overall profit.

The above objective function may evaluate the overall profit for one or more time periods, that is, evaluate the profit based on the data of the current time period, or evaluate the profit comprehensively based on the data of the current time period and the estimated data of a plurality of time periods in the future. In the embodiment of the present invention, the time period is set only for data statistics, for example, every 5 minutes may be used as a time period, and data acquired at any time point in the time period may be used as data corresponding to the time period.

The first order savings cost may be determined based on a first order amount in the order pool and a first order probability of the at least one order. The method specifically comprises the following steps: determining an average order combining probability of an order pool according to a first order combining probability of at least one order in the order pool; acquiring a first order quantity corresponding to a current time period, and determining a remaining second order quantity in an order pool after order placement according to the first order quantity, a first order quantity in the order pool and a first order placement quantity; a first order savings cost for the order pool is determined based on the second order quantity, the average order probability, and a second order savings cost for the unit order. The second order-to-order cost saving of the unit order is the cost saving brought by each order to be ordered, and the parameter is a value set for evaluating the overall profit and can be flexibly set according to the requirement.

The order-combining probability mentioned above refers to the probability that the same user is likely to place an order again and distribute to the same address for a certain order. The order-to-order cost savings is due to the reduction in logistics costs that result from combining multiple orders. For example, a user purchases a computer, and it is likely that after a while the user places an order to purchase a keyboard and mouse, the two subsequent orders can be combined with the computer order. In this case, if the computer order and the keyboard and mouse order are merged and delivered, the logistics cost can be saved, for example, the delivery time of the logistics worker, the logistics packaging cost, and the like can be saved.

For the order pool, it is desirable that orders with smaller order combining probability are placed to the downstream logistics system, and orders with larger order combining probability are left in the order pool to wait for orders of the same user to be combined, so as to improve the order combining cost as much as possible. Therefore, the order-saving cost of the entire order pool (i.e., the first order-saving cost) can be obtained by multiplying the remaining order amount waiting for the order (i.e., the second order amount) in the order pool after placing the order to the logistics system, the average order probability of the order pool, and the order-saving cost of the unit order (i.e., the second order-saving cost).

The first logistics capacity loss can be determined based on the second order quantity, the average order probability, and the second order cost savings for the unit order. The method specifically comprises the following steps: acquiring a capacity difference value between the first lower single quantity and the first logistics capacity; and determining the capacity loss of the first logistics according to the capacity difference and the capacity loss of the second logistics per unit capacity. The second commodity circulation energy loss of unit capacity is the capacity loss caused by each order exceeding the commodity circulation capacity or being insufficient in commodity circulation capacity, and the parameter is also a value set for evaluating the overall profit and can be flexibly set according to the requirement. The logistics capacity refers to the number of orders that the logistics system can process. The loss of the logistics capacity refers to the loss caused by the fact that the logistics system is not effectively utilized, and there are two losses, on one hand, the resources of the logistics system are completely or partially idle, which causes the loss of the capacity, and on the other hand, the orders processed by the logistics system are in an oversaturation state, that is, an order overstock exists, which in the logistics system reduces the operation efficiency of the logistics system, and the orders cannot be processed by the logistics system at any time, and if the orders are placed in an order pool, the possibility of order combination is obtained, so that the loss also exists in the case that the logistics system is oversaturated.

For the logistics system, it is desirable that the number of orders (first order quantity) issued from the order pool at a time exactly matches the current capacity (i.e. first logistics capacity), or the difference between the two should be as small as possible. Namely, after the logistics system receives the order, the logistics system can immediately or temporarily wait for carrying out logistics processing, packaging, logistics transportation and other processing, and before the order sent by the order pool is received, the logistics system is not idle for too long. The capacity of the physical system can be reported to the order processing system by the logistics system periodically.

In order to obtain a more suitable first order quantity, the embodiment of the present invention further adopts an iterative manner to comprehensively evaluate the order pool variation conditions of the current time period and the future time periods, so as to determine the order quantity currently required to be executed.

Specifically, the first contract cost may be determined by:

s1021: an average order probability for the order pool is determined based on the first order probability for at least one order in the order pool. The average listing probability in the current order pool will be taken as the listing probability for a number of time periods thereafter.

S1022: the method comprises the steps of obtaining a first order quantity corresponding to a current time period and predicting the first order quantity corresponding to a time period with a preset number in the future, obtaining the first order quantity in an order pool corresponding to the current time period, obtaining a first order quantity corresponding to the current time period, and predicting the first order quantity corresponding to the time period with the preset number in the future. In the embodiment of the invention, the incoming order quantity and the outgoing order quantity correspond to the time periods, and statistics and prediction are carried out according to the time periods. For example, every 5 minutes may be used as a time period for which a single quantity is counted or predicted. The unit amount of the current time period can be directly counted and obtained, and the unit amount of the future time period can be predicted based on historical data (such as data of the same time period in the previous day) or data change trend (such as unit amount change trend of the previous time periods). For the order quantity, the order quantity of the current time period is determined by the order processing system, the order quantity of a plurality of time periods in the future can be directly the same as the order quantity of the current time period, and the order quantity of the plurality of time periods in the future can be estimated based on the determined order quantity of the current time period and the previous time periods according to the data change trend. In the embodiment of the present invention, the next amount of the current time period is a value that is desired to be finally determined by the calculation processing of the objective function.

S1023: and determining the first order amount in the order pool of the next time period by taking the first order amount, the first next order amount and the first order amount in the order pool of the current time period as initial conditions, then determining the first order amount in the order pool of the next time period according to the predicted first order amount and the first next order amount corresponding to the next time period, and carrying out iteration processing until the time period of the preset number is reached. This part of the processing may refer to the above-described equation (2), i.e., the order amount at the start of the order pool in the latter time period (i.e., the first order amount) is determined by the case of the former time period. For example, in the first time period, there are 100 orders (first order quantity) in the order pool at the beginning, the order quantity determined by the order processing system is 50 orders (first order quantity), the order pool receives 30 new orders (first order quantity) in the first time period, so that it can be calculated that 80 orders remain in the order pool after the orders are placed to the logistics system at the end of the first time period, and the 80 orders are used as the initial order quantity in the order pool in the next time period, i.e. the first order quantity in the order pool in the second time period. And the first order amount for a plurality of time periods in the future have been predictively determined, whereby the first order amount for the order pool for the third time period may continue to be calculated, and so on, the first order amount for the order pool for all time periods may be calculated, and the first order amount for the order pool for each time period will ultimately be used to calculate the order savings cost.

S1024: a first order savings cost for the order pool is determined based on the first order quantity in the order pool, the average order probability, and the second order savings cost for the unit order for the current and future predetermined number of time periods. And the first order quantity of the order pool in each time period is obtained through the previous step, the order combining probability in each time period is considered to be the same as the average order combining probability in the current time period, and the cost which can be saved by the unit order if the unit order is combined is a given value, namely the cost is saved by the second order. Based on these data, the total available aggregate cost (i.e., the first aggregate cost) for the current and future time periods may be calculated by: the products of the first order quantity, the average order probability, and the second order cost savings for the unit order for each time period are then summed.

The first stream capacity loss can be determined by:

s1021': and acquiring first logistics capacity corresponding to the current and future preset number of time periods. The logistics capacity can be reported from a downstream logistics system, and the downstream logistics system can report the current logistics operation capacity and predict the capacity in the future time period according to the operation condition of the downstream logistics system, wherein the logistics capacity mainly refers to the number of orders capable of being processed.

And S1022': and determining the difference value of the logistics capacity of the current time period and the future time period of the preset quantity according to the first logistics capacity and the first next single quantity corresponding to the current time period and the future time period of the preset quantity. In the previous step, the next orders of the current and future time periods are obtained, and the difference of the logistics capacity corresponding to each time period can be calculated by combining the logistics capacity of the downstream logistics system of the current and future time periods obtained in the previous step, wherein the difference can be a positive number or a negative number, the positive number corresponds to the next order being larger than the capacity of the logistics system, and conversely, the next order is a negative number when the next order does not meet the downstream logistics capacity.

S1023': and determining the first logistics capacity loss according to the logistics capacity difference value of the current time period and the future time period and the second logistics capacity loss of unit capacity. After the difference between the placed order and the logistics system capacity is determined, the capacity loss of the whole amount of the current and future time periods (i.e. the first logistics capacity loss) can be calculated by combining the capacity, i.e. the capacity loss corresponding to the unit order. For example, if the downstream logistics system has capacity of 100 orders, the order processing system only issues 50 orders to the downstream logistics system, which results in idle waste of personnel, equipment and transportation tools of the downstream logistics system. Based on statistical processing in terms of cost, the capacity loss caused by each order can be obtained, and thus the loss caused by 50 orders can be calculated. On the other hand, if the capacity of the logistics system is over-saturated, new orders cannot be processed, which also affects the operation efficiency of the logistics system, and additional costs of manpower and material resources are needed to store the temporarily unprocessed orders, which involve additional costs. In addition, the orders which cannot be processed in time can be completely placed in the order pool to wait for order combination, and the cost of the logistics system can be reduced after the orders are combined, so that the orders which cannot be processed in time by the logistics system can cause capacity loss. The loss can also be counted out the capacity loss caused by the unit order, and then the logistics capacity loss can be calculated after the order quantity which is beneficial to the capacity of the logistics system is obtained. It should be noted that, in practical applications, the same calculation method may be used for the order quantity exceeding the logistics capacity (the logistics capacity is idle) and the order quantity being smaller than the logistics capacity (the logistics capacity is over-saturated), the logistics capacity loss corresponding to the unit capacity used in the two cases is the same, or different calculation methods may be used, and the logistics capacity loss corresponding to the unit capacity used in the two cases is used in the two cases.

S103: and selecting an order from the order pool according to the first order quantity, and placing the order to the logistics system. In the process of issuing the order to the logistics, the order of the selected first order issuing amount can be combined first, and then the order after the combination processing is issued to the logistics. Further, in this step, the orders in the order pool may be selected for placement based on the order probability. Specifically, the step may include: and ranking the orders according to the first order combining probability of each order in the order pool, then selecting the orders according to the ranking sequence of the first order combining probability from low to high, and executing the order issuing to the logistics system.

In the above description, the basic flow of the order processing method according to the embodiment of the present invention is introduced, and in a specific e-commerce field, the types of orders may be many, and the corresponding requirements may be different, so that different requirements may exist in the aspect of order combination processing. For example, there may be differences in the urgency of delivery of orders, some orders may require delivery on the day, some require delivery on the next day, and some may not have the time to deliver within three days. For another example, the order distribution mode is different, and the fresh goods can only be transported by a refrigerator car, so that the fresh goods cannot be distributed together with the common goods, and can only be distributed together with the fresh goods belonging to the same category. Based on such a situation, the embodiment of the present invention proposes a process that can group orders in an order pool and then individually execute the foregoing steps for each group. Specifically, after an order is generated, the order may be grouped according to the type of the product involved in the order and/or the delivery time requirement; then, the processes of the foregoing steps S101 to S103 are respectively performed for each of the order groups generated after grouping.

According to the order processing method provided by the embodiment of the invention, the number of the orders issued to the downstream logistics at present is dynamically determined based on the order combination probability of the orders in the order pool and the downstream logistics capacity condition, so that the balance between the order combination waiting of the orders in the order pool and the downstream logistics capacity matching is better maintained, the maximization of the whole benefit is realized, and the utilization rate of logistics resources is improved.

Example two

As shown in fig. 3, which is a schematic structural diagram of an order processing apparatus according to an embodiment of the present invention, the apparatus may be applied to an e-commerce platform or a logistics system, and the apparatus may specifically include:

the data obtaining module 11 is configured to obtain a first order quantity in the current order pool, a first order combining probability of at least one order, and a first logistics capacity.

And the order placing quantity determining module 12 is configured to determine a first order placing quantity, which needs to perform order placing processing on the logistics for the current order pool, according to the first order combining probability and the first logistics capacity.

Specifically, in this step, a first order quantity required to perform the order placing to the logistics for the current order pool is determined through a predetermined objective function, and the objective function determines the overall profit according to the first order saving cost of the order pool and the first logistics capacity loss. Wherein the first order cost savings is determined based on a first order quantity in the order pool and a first order probability of the at least one order, and the first logistics capacity loss is determined based on a degree of matching of the first logistics capacity to the first order quantity.

And the order placing processing module 13 is configured to select an order from the order pool according to the first order placing amount, and perform order placing processing on the logistics system. In the process of issuing the order to the logistics, the order of the selected first order issuing amount can be combined first, and then the order after the combination processing is issued to the logistics. In addition, orders in the order pool can be selected to be placed based on the order combining probability. Specifically, the processing may include: and ranking the orders according to the first order combining probability of each order in the order pool, then selecting the orders according to the ranking sequence of the first order combining probability from low to high, and executing the order issuing to the logistics system.

The detailed description of the above processing procedure, the detailed description of the technical principle, and the detailed analysis of the technical effect are described in the foregoing embodiments, and are not repeated herein.

The order processing device in the embodiment of the invention dynamically determines the number of orders issued to the downstream logistics at present based on the order combination probability of the orders in the order pool and the downstream logistics capacity condition, thereby better maintaining the balance between the order combination waiting of the orders in the order pool and the downstream logistics capacity matching, realizing the maximization of the whole profit and improving the utilization rate of logistics resources.

EXAMPLE III

As shown in fig. 4, it is a schematic structural diagram of an order processing system according to an embodiment of the present invention, and the system includes:

the order combining probability estimation module 21 is configured to receive orders generated by the e-commerce trading platform, store the orders into an order pool, periodically perform order combining probability estimation on the orders in the order pool, and provide a first order combining probability for generating at least one order to the order placing quantity decision module. The order probability estimation module 21 may use the order probability estimation model described in fig. 1, so as to perform the calculation process related to the order probability.

And the order quantity decision module 22 is configured to obtain the predicted first incoming order quantity, the predicted first logistics capacity and the predicted first order quantity in the order pool from the e-commerce trading platform, the logistics system and the order pool, determine a first order quantity to be processed for issuing an order to logistics for the current order pool according to the first incoming order quantity, the first logistics capacity, the predicted first order quantity in the order pool and the predicted first order quantity in the order pool, and determine the first order quantity to be processed for issuing an order to logistics for the current order pool, and send the first order quantity to the order pool. The order quantity decision module 22 may use the order quantity decision model described above with respect to fig. 1 to determine the first order quantity.

And the order pool 23 is used for caching orders, ranking the orders and the first order taking amount according to the first order combining probability of at least one order, selecting the orders and sending the orders to the order taking execution module.

And the order placing execution module 24 is configured to combine the received orders and send the combined orders to the logistics system.

Example four

Fig. 5 is a second flowchart of the order processing method according to the second embodiment of the present invention, which shows an interaction process between the user side and the server, and includes:

s201: and receiving a list combination inquiry message aiming at the existing order from the server. The server referred to herein may be an order processing system as shown in fig. 1, which may send a message to a user corresponding to an order already in the order pool asking if a new item order is to be generated and possibly, so that a decision may be made whether to leave the order in the order pool to await a close order.

S202: and returning a list feedback message to the server, wherein the list feedback message comprises one or more items of information of whether a list exists, the commodities to be listed and the waiting time of the list. In step S202, the specific content in the order feedback message may be obtained as follows:

1) determining, based on the user operation behavior: and acquiring the operation behavior information of the user, generating a bill combination feedback message according to the operation behavior information, and returning the bill combination feedback message to the server. For example, whether the user is likely to place an order again or not may be determined by collecting a currently viewed page of the item.

2) Determining, based on the user's direct response: and generating a bill feedback message in response to the content aiming at the bill inquiry message input by the user in the interactive interface, and returning the bill feedback message to the server. The content of the message input by the user may be a specific name of the commodity or text information indicating that the user wants to continue purchasing other commodities.

Fig. 6 is a third schematic flowchart of an order processing method according to an embodiment of the present invention, where the third schematic flowchart shows an interaction process between the server and the user side, and the interaction process includes:

s301: and sending a bill combination inquiry message to the user side. As previously described, the server may be the order processing system shown in fig. 1, and the order processing system may send a query message to the user corresponding to the order in the order pool to query that a new product order is generated and possibly.

S302: receiving an order feedback message from a user side, and determining a first order combining probability of the order of the user in the order pool according to the order feedback message, wherein the order feedback message comprises one or more items of information of whether an order exists, a commodity to be combined and the order combining waiting time. The order processing system receives the order feedback message, and can determine the first order combining probability of the order based on the information, and the adjustment of the high and low of the first order combining probability is equivalent to indirectly adjusting the time of the order left in the order pool. For example, if the user-side feedback message indicates that the user is performing a new order transaction and provides information about related goods, it is determined that the user can combine the new order with the existing orders in the order pool, and in this case, the first order combining probability becomes very high, so that the orders are left in the order pool as much as possible to wait for order combining.

On the basis of determining the first order combining probability, the order processing system may further continue to execute the specific flow of the order processing method in the first embodiment, and detailed descriptions of the processing procedure, the technical principle, and the technical effect are described in the first embodiment in detail, and are not described herein again.

Fig. 7 is a fourth flowchart of the order processing method according to the embodiment of the present invention, which illustrates an interaction process with a server at a logistics system side, and includes:

s401: and receiving a logistics situation inquiry message from the server. The server may be the order processing system shown in fig. 1, and the order processing system may periodically send query messages to the downstream logistics system, so as to know the operation state of the logistics system in time, and thus make decisions on the order placing process of the order pool.

S402: and determining the available order quantity and/or the order logistics processing waiting time according to the current logistics capacity and the quantity of unprocessed orders. After receiving the inquiry message, the logistics system can acquire the current logistics operation condition, and determine the number of orders which can be currently processed, namely the current logistics capacity, and the backlog condition of the orders, namely the number of unprocessed orders. S403: and feeding back a logistics state feedback message containing the number of available orders and/or the order logistics processing waiting time to the server. The logistics system feeds back the information to the order processing system in the form of feedback information so that the order processing system can make a decision on order placing processing.

In addition, the logistics system also receives the order issued by the server and executes the logistics processing of the order.

Fig. 8 is a fifth flowchart of the order processing method according to the embodiment of the present invention, which shows an interaction process with a logistics system at the server side, and includes:

s501: and sending a logistics condition inquiry message to the logistics system. The server referred to herein may be the order processing system shown in fig. 1. The order processing system can periodically send inquiry messages to the downstream logistics system, so that the running state of the logistics system can be known in time.

S502: receiving a logistics situation feedback message containing the number of available orders and/or the order logistics processing waiting time from the logistics system.

S503: and determining the first logistics capacity of the logistics system according to the available order quantity and/or the order logistics processing waiting time. The order processing system determines the first logistics capacity according to the logistics status feedback message reported by the logistics system, and the level of the first logistics capacity can indirectly adjust the time of the order left in the order pool. For example, if the amount of available orders reported by the downstream logistics system is low and/or the order logistics processing waiting time is long, this indicates that the logistics capacity of the current logistics system is saturated or overloaded, and in this case, it is more beneficial to leave the orders in the order pool to wait for the orders to be combined.

On the basis of determining the first logistics capacity, the order processing system may further continue to execute the specific flow of the order processing method according to the first embodiment, and detailed descriptions of the processing process, the technical principle, and the technical effect are described in detail in the first embodiment, and are not repeated herein.

It should be noted that, in this embodiment, the order processing system as the server side may periodically send query messages to the user side and the logistics system side, so as to grasp the possible order combination situation of the user side and the operation capacity of the downstream logistics system in real time, and control the order placing process of the orders in the order pool, so as to maintain a good balance between waiting for order combination and executing order placing, and achieve a good comprehensive benefit.

EXAMPLE five

The foregoing embodiment describes a flow process and a device structure of an order processing method, and the functions of the method and the device can be implemented by an electronic device, as shown in fig. 9, which is a schematic structural diagram of the electronic device according to an embodiment of the present invention, and specifically includes: a memory 110 and a processor 120.

And a memory 110 for storing a program.

In addition to the programs described above, the memory 110 may also be configured to store other various data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device, contact data, phonebook data, messages, pictures, videos, and so forth.

The memory 110 may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

The processor 120, coupled to the memory 110, is used for executing the program in the memory 110 to perform the operation steps of the order processing method described in the foregoing embodiments.

Further, the processor 120 may also include various modules described in the foregoing embodiments to perform processing for an order, and the memory 110 may be used, for example, to store data required by the modules to perform operations and/or data output.

Further, as shown, the electronic device may further include: communication components 130, power components 140, audio components 150, display 160, and other components. Only some of the components are schematically shown in the figure and it is not meant that the electronic device comprises only the components shown in the figure.

The communication component 130 is configured to facilitate wired or wireless communication between the electronic device and other devices. The electronic device may access a wireless network based on a communication standard, such as WiFi, a mobile communication network, such as 2G, 3G, 4G/LTE, 5G, or a combination thereof. In an exemplary embodiment, the communication component 130 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 130 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

The power supply component 140 provides power to the various components of the electronic device. The power components 140 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for an electronic device.

The audio component 150 is configured to output and/or input audio signals. For example, the audio component 150 includes a Microphone (MIC) configured to receive external audio signals when the electronic device is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory 110 or transmitted via the communication component 130. In some embodiments, audio assembly 150 also includes a speaker for outputting audio signals.

The display 160 includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The aforementioned program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An order processing method, comprising:

2. The method of claim 1, wherein determining a first order quantity that requires performing a logistics order placement process on a current order pool based on the first joint probability and the first logistics capacity comprises:

determining a first order quantity required to perform order placing processing to logistics for a current order pool through a preset objective function, wherein the objective function determines overall profit according to a first order saving cost of the order pool and a first logistics capacity loss, the first order saving cost is determined according to the first order quantity in the order pool and a first order combining probability of at least one order, and the first logistics capacity loss is determined according to the matching degree of the first logistics capacity and the first order quantity.

3. The method of claim 2, wherein the first order savings cost determination based on the first order amount in the order pool and the first order probability of the at least one order comprises:

determining an average order combining probability of an order pool according to a first order combining probability of at least one order in the order pool;

acquiring a first order quantity corresponding to a current time period, and determining a remaining second order quantity in an order pool after order placement according to the first order quantity, a first order quantity in the order pool and the first order quantity;

and determining the first order saving cost of the order pool according to the second order quantity, the average order combining probability and the second order saving cost of the unit order.

4. The method of claim 2, wherein determining the first logistics capacity loss based on how well the first logistics capacity matches the first next quantity comprises:

acquiring a capacity difference value between a first lower single quantity and the first logistics capacity;

and determining the first logistics capacity loss according to the capacity difference and the second logistics capacity loss of unit capacity.

5. The method of claim 1, wherein selecting an order from the pool of orders according to the first order placement quantity, performing the order placement to the logistics system comprises:

and ranking the orders according to the first order taking amount and the first order combining probability of at least one order in the order pool, and placing the orders to the logistics system according to the ranking sequence of the first order combining probability from low to high.

6. The method of claim 2, wherein the first order savings cost determination from a first order amount in an order pool and a first order probability of at least one order comprises:

acquiring a first order quantity corresponding to a current time period and predicting the first order quantity corresponding to a time period with a preset number in the future, acquiring the first order quantity in an order pool corresponding to the current time period, acquiring a first order quantity corresponding to the current time period, and predicting the first order quantity corresponding to the time period with the preset number in the future;

determining a first order amount in an order pool of a next time period by taking a first order amount, a first next order amount and a first order amount in the order pool of the current time period as initial conditions, then determining the first order amount in the order pool of the next time period according to the predicted first order amount and the first next order amount corresponding to the next time period, and carrying out iterative processing until a predetermined number of time periods are reached;

a first order savings cost for the order pool is determined based on the first order quantity in the order pool, the average order probability, and a second order savings cost for the unit order for the current and future predetermined number of time periods.

7. The method of claim 6, wherein determining the first logistics capacity loss based on how well the first logistics capacity matches the first next quantity comprises:

acquiring first logistics capacity corresponding to the current and future predetermined number of time periods;

determining the difference value of the logistics capacity of the current time period and the future time period with the preset number according to the first logistics capacity and the first next single amount corresponding to the current time period and the future time period with the preset number;

and determining the first logistics capacity loss according to the logistics capacity difference value of the current time period and the future time period and the second logistics capacity loss of unit capacity.

8. An order processing method, comprising:

9. An order processing method, comprising:

10. The method of claim 9, wherein returning the round-list feedback message to the server comprises:

collecting operation behavior information of a user, generating an order feedback message according to the operation behavior information, and returning the order feedback message to the server;

and/or the presence of a gas in the gas,

and generating a bill combination feedback message in response to the content input by the user in the interactive interface aiming at the bill combination inquiry message, and returning the bill combination feedback message to the server.

11. An order processing method, comprising:

sending a bill combination inquiry message to a user side;

12. The method of claim 11, further comprising:

acquiring a first order quantity in a current order pool, the first order combining probability of at least one order and first logistics capacity;

13. An order processing method, comprising:

receiving a logistics situation inquiry message from a server;

14. The method of claim 13, further comprising:

and receiving the order issued by the server and executing the logistics processing of the order.

15. An order processing method, comprising:

sending a logistics condition inquiry message to a logistics system;

and determining a first logistics capacity of the logistics system according to the available order quantity and/or the order logistics processing waiting time.

16. The method of claim 15, further comprising:

acquiring a first order quantity in a current order pool, the first order combining probability of at least one order and the first logistics capacity;

17. An order processing apparatus comprising:

18. The apparatus of claim 17, wherein determining a first order quantity that requires performing a logistics order placement process on a current order pool based on the first joint probability and the first logistics capacity comprises:

determining a first order quantity to be processed for issuing orders to logistics for the current order pool through a preset objective function, wherein the objective function determines the overall profit according to a first order saving cost of the order pool and a first logistics capacity loss, the first order saving cost is determined according to the first order quantity in the order pool and a first order combining probability of each order, and the first logistics capacity loss is determined according to the matching degree of the first logistics capacity and the first order quantity.

19. An order processing system comprising:

20. An electronic device, comprising:

a memory for storing a program;

a processor for executing the program stored in the memory to perform the order processing method of any of claims 1 to 7.