CN115936576A

CN115936576A - Distribution balancing method and device for warehouse

Info

Publication number: CN115936576A
Application number: CN202211530707.4A
Authority: CN
Inventors: 周超越; 高振羽; 庄晓天; 吴盛楠
Original assignee: Beijing Jingdong Shangke Information Technology Co Ltd; Beijing Jingdong Zhenshi Information Technology Co Ltd
Current assignee: Beijing Jingdong Shangke Information Technology Co Ltd; Beijing Jingdong Zhenshi Information Technology Co Ltd
Priority date: 2022-12-01
Filing date: 2022-12-01
Publication date: 2023-04-07

Abstract

The disclosure relates to a distribution balancing method and device of a warehouse and a non-volatile computer readable storage medium, and relates to the technical field of logistics. The equalization method comprises the following steps: and establishing a balance model by taking at least one of the conditions of meeting the minimum holding quantity of goods in the warehouse, balancing the delivery quantity among the warehouses in charge of allocation, minimizing the valid lead VLT of delivery or balancing the delivery quantity among the warehouses in charge of allocation as a balance target, wherein the balance model comprises at least one decision variable related to the delivery information of the warehouse and is used for configuring the delivery information of the warehouse. The technical scheme of the disclosure can improve the balance performance.

Description

Distribution balancing method and device for warehouse

Technical Field

The present disclosure relates to the field of logistics technologies, and in particular, to a distribution balancing method for a warehouse, a distribution balancing apparatus for a warehouse, and a non-volatile computer-readable storage medium.

Background

The logistics service company provides supply chain services, namely warehousing, distribution and transportation of products, for the B-end client. The logistics service company can provide warehousing services for customers, store the goods of the customers in warehouses of the logistics service company all over the country so as to cover the customer demands in each area, and provide distribution services.

As the demand of customers may be different in different areas, uneven supply and demand may occur in each warehouse. For example, a certain product may be out of stock at warehouse A, but may be overstocked at warehouse B. As a result, the consumer covered by warehouse A either cannot purchase the good, and thus end B customers lose sales profits; or the customer successfully places an order, but the goods are shipped from a warehouse in another area (e.g., warehouse B), resulting in higher logistics costs and longer fulfillment time.

Therefore, in order to increase sales profits of the B-side customer, reduce delivery costs of the supply chain, and increase delivery timeliness, it is desirable to perform an inventory balancing plan for goods among multiple warehouses before a warehouse becomes out of stock or overstocked. It can be seen that the balance between warehouses is fundamentally to balance inventory supply and consumption.

In the related art, a plurality of warehouses are equalized with the aim of minimizing various costs involved in warehousing.

Disclosure of Invention

The inventors of the present disclosure found that the following problems exist in the related art described above: many costs cannot be obtained or accurate estimation is difficult, and an equalization model is not in accordance with the actual situation, so that the equalization performance is reduced.

In view of this, the present disclosure provides a distribution balancing technical solution for a warehouse, which can improve balancing performance.

According to some embodiments of the present disclosure, there is provided a delivery balancing method for a warehouse, including: establishing a balance model by taking at least one of the requirements of the lowest holding quantity of goods in the warehouse, the balance of the delivery quantity among the warehouses in charge of allocation, the minimum Valid Lead Time (VLT) of delivery or the balance of the delivery quantity among the warehouses in charge of allocation as a balance target, wherein the balance model comprises at least one decision variable related to the delivery information of the warehouses and is used for configuring the delivery information of the warehouses.

In some embodiments, building the equalization model comprises: an objective function of the equalization model is established based on at least one of whether a minimum hold of the goods in the plurality of warehouses is met, whether the warehouses responsible for the allocation are equalized, whether the VLT's or the warehouses responsible for the allocation are equalized, the objective function including at least one decision variable.

In some embodiments, the equalization method further comprises: solving the equilibrium model by taking the value of the minimized objective function as a solving target so as to determine the value of at least one decision variable; and configuring the distribution information of each warehouse according to the value of at least one decision variable.

In some embodiments, establishing an objective function of the equalization model comprises: establishing a first target item according to whether the minimum holding quantity of goods in a plurality of warehouses is met, establishing a second target item according to whether the warehouses in charge of allocation are balanced, establishing a third target item according to the VLT, and establishing a fourth target item according to whether the warehouses in charge of allocation are balanced; and establishing an objective function according to the weighted sum of the first objective item, the second objective item, the third objective item and the fourth objective item.

In some embodiments, establishing the first target item based on whether a minimum hold of the goods in the plurality of warehouses is met comprises: the first objective item is established based on the number of warehouses responsible for distribution that the inventory cannot meet the minimum hold after the distribution of the goods.

In some embodiments, establishing the second target item based on whether there is a balance between the warehouses responsible for allocation includes: and establishing a second target item according to the difference of the satisfaction conditions of the target inventory among the warehouses which are responsible for distribution after distribution.

In some embodiments, establishing the second target item comprises: and determining the satisfaction condition of the target inventory according to the current goods quantity, the distribution demand quantity and the actual distribution quantity of any warehouse in charge of distribution, wherein the satisfaction condition of the target inventory is inversely related to the sum of the current goods quantity and the distribution demand quantity and positively related to the sum of the current goods quantity and the actual distribution quantity.

In some embodiments, establishing the third target item in dependence upon the VLT comprises: the third target item is determined based on a number of VLTs between the warehouse responsible for check-in and the warehouse responsible for check-out that have a delivery relationship.

In some embodiments, determining the third target item comprises: the third target term is determined based on a difference between each VLT and a maximum value of the VLTs.

In some embodiments, establishing the fourth target item based on whether there is a balance between the warehouses responsible for allocation includes: and establishing a fourth target item according to the difference of the remaining inventory information among the warehouses which are responsible for distribution after distribution.

In some embodiments, establishing the fourth target item comprises: and determining residual inventory information according to the difference between the current cargo quantity and the dispensing quantity of any one warehouse in charge of dispensing after delivery and the maximum value of the current cargo quantities of all warehouses in charge of dispensing, wherein the residual inventory information is positively correlated with the difference between the current cargo quantity and the dispensing quantity and is negatively correlated with the maximum value of the current cargo quantity.

In some embodiments, the first target term is weighted more heavily than the second target term, which is weighted more heavily than the third target term, which is weighted more heavily than the fourth target term.

In some embodiments, the second target item is weighted according to the number of warehouses responsible for check-in, and the fourth target item is weighted according to the number of warehouses responsible for check-in and a maximum value of the VLTs between the warehouses responsible for check-in and the warehouses responsible for check-out having a delivery relationship.

In some embodiments, establishing the equalization model comprises at least one of: determining a first constraint condition according to the current goods quantity, the actual distribution quantity, the minimum reserve quantity and the distribution demand quantity of a warehouse in charge of distribution and whether the delivered inventory quantity meets the minimum reserve quantity or not; determining a second constraint condition according to the fact that the actual dispensing amount of the warehouse in charge of dispensing does not exceed the dispensing demand amount; determining a third constraint condition according to the fact that the actual allocation amount of the warehouse in charge of the allocator does not exceed the allocation demand; determining a fourth constraint condition according to the fact that the allocation amount of the warehouse in charge of allocation with the distribution relation does not exceed the maximum value of the allocation demand of all warehouses in charge of allocation; determining a fifth constraint condition according to the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution, the weighted sum of the actual distribution quantities of all the warehouses responsible for distribution, the balance demand quantity and whether the distribution demand quantities of all the warehouses responsible for distribution meet or not, wherein the balance demand quantity comprises the maximum value of the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution and the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution; determining a sixth constraint condition according to whether the weighted sum of the allocation demand quantities of all the warehouses in charge of allocation, the weighted sum of the actual allocation quantities of all the warehouses in charge of allocation, the balanced demand quantity and the allocation demand quantities of all the warehouses in charge of allocation meet or not; or determining a seventh constraint condition according to whether the distribution demand of all warehouses in charge of distribution is met or not and whether the distribution demand of all warehouses in charge of distribution is met or not.

In some embodiments, the equalization method further comprises: solving an initial solution of the equilibrium model by using a greedy algorithm; adjusting the initial solution according to the satisfying condition of the allocation demand of each warehouse in charge of allocation in the initial solution, or at least one item of VLT between the warehouse in charge of allocation and the warehouse in charge of allocation with a delivery relationship in the initial solution; and determining a final solution of the equilibrium model according to the adjustment result.

In some embodiments, adjusting the initial solution comprises: adjusting the distribution relation in the initial solution; calculating whether the value of the target function of the equilibrium model is improved or not according to the adjustment result; and determining a final solution of the equalization model according to the adjustment result under the condition of improvement.

In some embodiments, solving for an initial solution for the equalization model comprises: performing initial solution updating according to whether the current total allocation amount is greater than or equal to the total allocation amount and whether a warehouse which is responsible for allocation and does not meet the lowest reserve amount exists; according to whether a warehouse in charge of allocation exists in the allocation bin set or not, the allocation requirement of one warehouse in charge of allocation can be met independently, and initial solution updating is continued; and utilizing the allowable amount of the rest warehouse in charge of allocation corresponding to the updated initial solution to meet the allocation amount requirement of the rest warehouse in charge of allocation until the allowable amount of the rest warehouse in charge of allocation is reduced to 0 or the allocation amount requirement of the rest warehouse in charge of allocation is reduced to 0, so as to continue the initial solution updating.

According to other embodiments of the present disclosure, there is provided a distribution balancing apparatus for a warehouse, including: a determining unit, configured to determine, as a balance target, at least one of a minimum holding amount of goods in the warehouse, a balance of delivery amounts between warehouses responsible for allocation, a minimum VLT of delivery, or a balance of delivery amounts between warehouses responsible for allocation; the system comprises a building unit, a balancing unit and a control unit, wherein the building unit is used for building a balancing model according to a balancing target, the balancing model comprises at least one decision variable related to warehouse delivery information, and the balancing model is used for configuring the warehouse delivery information.

In some embodiments, the establishing unit establishes an objective function of the equilibrium model based on at least one of whether a minimum hold of the goods in the plurality of warehouses is met, whether the warehouses responsible for allocation are balanced, the VLT, or the warehouses responsible for allocation are balanced, the objective function including at least one decision variable.

In some embodiments, the equalizing means further comprises: the solving unit is used for solving the equilibrium model by taking the value of the minimized objective function as a solving target so as to determine the value of at least one decision variable; and configuring the distribution information of each warehouse according to the value of at least one decision variable.

In some embodiments, the establishment unit establishes a first target item according to whether a minimum holding amount of the goods in the plurality of warehouses is satisfied, establishes a second target item according to whether the warehouses responsible for allocation are balanced, establishes a third target item according to the VLT, and establishes a fourth target item according to whether the warehouses responsible for allocation are balanced; and establishing an objective function according to the weighted sum of the first objective item, the second objective item, the third objective item and the fourth objective item.

In some embodiments, the establishing unit establishes the first target item based on the number of warehouses responsible for check-in for which the inventory cannot meet the minimum holding amount after the goods are checked-in.

In some embodiments, the establishing unit establishes the second target item based on a difference in satisfaction of the target inventory between the respective warehouses responsible for the allocation after the delivery.

In some embodiments, the establishing unit determines the satisfaction condition of the target inventory according to the current cargo quantity, the allocation required quantity and the actual allocation quantity of any warehouse in charge of allocation, wherein the satisfaction condition of the target inventory is negatively related to the sum of the current cargo quantity and the allocation required quantity and positively related to the sum of the current cargo quantity and the actual allocation quantity.

In some embodiments, the establishment unit determines the third target item based on a plurality of VLTs between the warehouse responsible for check-in and the warehouse responsible for check-out having the delivery relationship.

In some embodiments, the establishment unit determines the third target term according to a difference between each VLT and a maximum value among the VLTs.

In some embodiments, the creating unit creates the fourth target item based on a difference in remaining inventory information between the warehouses each of which is responsible for dispensing after delivery.

In some embodiments, the establishing unit determines the remaining inventory information according to a difference between the quantity of the present goods and the quantity of the dispensed goods of any one of the warehouses responsible for dispensing after delivery and a maximum value of the quantity of the present goods of all the warehouses responsible for dispensing, wherein the remaining inventory information is positively correlated with the difference between the quantity of the present goods and the quantity of the dispensed goods and is negatively correlated with the maximum value of the quantity of the present goods.

In some embodiments, the weight of the second target item is determined based on the number of warehouses responsible for check-in, and the weight of the fourth target item is determined based on the number of warehouses responsible for check-in and a maximum value of the plurality of VLTs between the warehouse responsible for check-in and the warehouse responsible for check-out having a delivery relationship.

In some embodiments, the establishing unit performs at least one of: determining a first constraint condition according to the current goods quantity, the actual distribution quantity, the minimum reserve quantity and the distribution demand quantity of a warehouse in charge of distribution and whether the delivered inventory quantity meets the minimum reserve quantity or not; determining a second constraint condition according to the fact that the actual dispensing amount of the warehouse in charge of dispensing does not exceed the dispensing demand amount; determining a third constraint condition according to the fact that the actual allocation amount of the warehouse in charge of the allocator does not exceed the allocation demand; determining a fourth constraint condition according to the fact that the allocation amount of the warehouse in charge of allocation with the distribution relation does not exceed the maximum value of the allocation demand of all warehouses in charge of allocation; determining a fifth constraint condition according to the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution, the weighted sum of the actual distribution quantity of all the warehouses responsible for distribution, the equilibrium demand quantity and whether the distribution demand quantities of all the warehouses responsible for distribution meet or not, wherein the equilibrium demand quantity comprises the maximum value of the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution and the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution; determining a sixth constraint condition according to whether the weighted sum of the allocation demand quantities of all the warehouses in charge of allocation, the weighted sum of the actual allocation quantities of all the warehouses in charge of allocation, the balanced demand quantity and the allocation demand quantities of all the warehouses in charge of allocation meet or not; or determining a seventh constraint condition according to whether the distribution demand of all warehouses in charge of distribution is met or not and whether the distribution demand of all warehouses in charge of distribution is met or not.

In some embodiments, the solving unit solves the initial solution of the equilibrium model by using a greedy algorithm; adjusting the initial solution according to the satisfying condition of the allocation demand of each warehouse in charge of allocation in the initial solution, or at least one item of VLT between the warehouse in charge of allocation and the warehouse in charge of allocation with a distribution relation in the initial solution; and determining a final solution of the equilibrium model according to the adjustment result.

In some embodiments, the solution unit adjusts the delivery relationship in the initial solution; calculating whether the value of the target function of the equilibrium model is improved or not according to the adjustment result; and determining a final solution of the equilibrium model according to the adjustment result in the case of improvement.

In some embodiments, the solving unit performs the initial solution update according to whether the current total allocation amount is greater than or equal to the total allocation amount and whether a warehouse in charge of allocation which does not meet the minimum holding amount exists; according to whether a warehouse in charge of allocation exists in the allocation bin set or not, the allocation requirement of one warehouse in charge of allocation can be met independently, and initial solution updating is continued; and utilizing the allowable amount of the rest warehouse in charge of allocation corresponding to the updated initial solution to meet the allocation amount requirement of the rest warehouse in charge of allocation until the allowable amount of the rest warehouse in charge of allocation is reduced to 0 or the allocation amount requirement of the rest warehouse in charge of allocation is reduced to 0, so as to continue the initial solution updating.

According to still other embodiments of the present disclosure, there is provided a distribution balancing apparatus for a warehouse, including: a memory; and a processor coupled to the memory, the processor configured to perform a method of distribution balancing of a warehouse in any of the above embodiments based on instructions stored in the memory device.

According to still further embodiments of the present disclosure, there is provided a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a delivery balancing method for a warehouse in any of the above embodiments.

In the above embodiment, the warehouses are balanced according to the minimum holding capacity, the balance among the warehouses, and the factor that the VLT can be accurately acquired. Therefore, the balance model which accords with the actual situation can be established, and the balance performance is improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.

The present disclosure may be understood more clearly from the following detailed description, taken with reference to the accompanying drawings,

wherein:

fig. 1 illustrates a flow diagram of some embodiments of a delivery balancing method of a warehouse of the present disclosure;

fig. 2 shows a flow chart of some embodiments of step 130 of the present disclosure;

FIG. 3 illustrates a schematic diagram of some embodiments of a delivery balancing method of a warehouse of the present disclosure;

FIG. 4 illustrates a block diagram of some embodiments of a distribution balancing apparatus of a warehouse of the present disclosure;

FIG. 5 illustrates a block diagram of further embodiments of a distribution equalization apparatus of a warehouse of the present disclosure;

fig. 6 illustrates a block diagram of still further embodiments of a distribution balancing apparatus of a warehouse of the present disclosure.

Detailed Description

Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of parts and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.

Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.

Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be discussed further in subsequent figures.

As previously mentioned, the so-called costs may include warehousing costs, holding costs, shipping costs, stock out costs, and the like. However, in an actual business scenario, the holding cost, the out-of-stock cost, etc. are difficult to measure. Furthermore, some of the costs (e.g., cost of goods, etc.) are unavailable, and thus it is impractical to model with the goal of minimizing the cost to address the need for equalization in real business. Therefore, inventory balancing of a warehouse requires balanced modeling in combination with actual business needs to balance different business goals.

Aiming at the technical problems, the balance model constructed by the method disclosed by the invention is more suitable for actual service scenes, and the optimization targets comprise the requirement of the minimum holding capacity of a distribution warehouse (a warehouse in charge of distribution), reduction of allocation times among warehouses, distribution quantity of a balance distribution warehouse (a warehouse in charge of distribution), distribution quantity of a balance distribution warehouse and the like.

In some embodiments, a multi-target inventory balancing model is constructed by combining a specific inventory balancing service scene and considering actual inter-bin balancing targets; and solving the constructed model by utilizing a solver.

In addition, the intelligent supply chain system calls the additional debugging strategy pool in an HTTP service form, certain requirements are imposed on the calculation time of the algorithm, an upper limit is set on the solving time of the solver, and the solving quality of the solver is correspondingly reduced along with the problem scale expansion in the later period.

Therefore, in consideration of the operation time of the HTTP (HyperText Transfer Protocol) service call equilibrium model, the heuristic solving algorithm of the inventory equilibrium model is designed in the present disclosure to obtain a higher quality solution under the condition of a larger problem scale.

In some embodiments, a heuristic solving algorithm for inter-bin equalization is designed to act as a solving algorithm as the problem grows in size. By comparing with the solving result of the solver, the heuristic algorithm can reduce the solving time and improve the accuracy of the optimal solution.

For example, the technical solution of the present disclosure can be realized by the following embodiments.

Fig. 1 illustrates a flow diagram of some embodiments of a delivery balancing method of a warehouse of the present disclosure.

As shown in fig. 1, in step 110, at least one of satisfying the minimum hold of the goods in the warehouse, balancing the delivery amount between warehouses responsible for allocation, minimizing the VLT of delivery, or balancing the delivery amount between warehouses responsible for allocation is determined as the balancing target.

In some embodiments, the objective function of the equalization model is established based on at least one of whether a minimum hold of the goods in the plurality of warehouses is met, whether there is an equalization between warehouses responsible for allocation, the VLT, or whether there is an equalization between warehouses responsible for allocation. The objective function includes at least one decision variable.

In some embodiments, the first target item is established based on whether a minimum holding quantity of the goods in the plurality of warehouses is met. For example, the first objective item is established based on the number of warehouses responsible for check-in that the inventory cannot meet the minimum holding amount after check-in of goods.

For example, the first target term may be determined by the following formula:

j is the number of the allocated bin.

For indicating whether the inventory of the joining bin j after the goods have been joined is below its minimum hold value, and/or whether it is greater than its minimum hold value>

Indicates a below minimum hold value, is>

Indicating that it is not below the minimum hold.

In some embodiments, the second target item is established based on whether there is a balance between the warehouses responsible for the allocation. For example, the second target item is established based on the difference in satisfaction of the target inventory between the warehouses responsible for the allocation after the delivery.

For example, the satisfaction condition of the target inventory is determined based on the present quantity, the distribution demand and the actual distribution quantity of any warehouse in charge of distribution, and the satisfaction condition of the target inventory is inversely related to the sum of the present quantity and the distribution demand and positively related to the sum of the present quantity and the actual distribution quantity.

For example, the second target term may be determined by the following formula:

for indicating a matched bin j ₁ And a loading bin j ₂ The target inventory of (1) is satisfied.

For example,

can be according to the matched bin j ₁ 、j ₂ Spot size>

And &>

Dispensing from a dispensing bin i to a dispensing bin j ₁ 、j ₂ Is based on the cargo quantity>

And &>

Admission bin j ₁ 、j ₂ Based on the matching-in demand amount (i.e., the matching-out amount)>

And &>

And (4) determining.

And &>

And

a negative correlation with->

And &>

Is positively correlated with the sum, and->

And each->

Is positively correlated with the sum, and->

And each>

And inversely correlated with the sum. In some embodiments, the third target item is established based on the VLT. For example, the third target item is determined based on a number of VLTs between the warehouse responsible for check-in and the warehouse responsible for check-out that have a delivery relationship. />

For example, the third target term is determined according to a difference between each VLT and a maximum value among the VLTs.

For example, the third target item may be based on whether or not dispense bin i dispenses inventory (i.e., whether or not a delivery relationship exists) to dispense bin j _ij VLTv from match bin i to match bin j _ij 、

And (4) determining. y is _ij =1 indicates delivery relationship exists, y _ij =0 indicates that there is no delivery relationship, device for selecting or keeping>

Is a set of dispensing bins. Third target item and y _ij Is positively correlated with v _max And v _ij Sum positively correlated with v _max A negative correlation.

In some embodiments, the fourth target item is established based on whether there is a balance between the warehouses responsible for allocation. For example, the fourth target item is established according to the difference of the remaining inventory information between the warehouses responsible for the allocation after the delivery.

For example, the surplus inventory information is determined according to the difference between the current quantity and the distribution quantity of any warehouse in charge of distribution after delivery and the maximum value of the current quantity of all warehouses in charge of distribution, and the surplus inventory information is positively correlated with the difference between the current quantity and the distribution quantity and negatively correlated with the maximum value of the current quantity.

For example, the fourth target term may be determined by the following formula:

for indicating dispensing bin i ₁ And a dispensing bin i ₂ The difference between remaining inventory information. E.g., based on>

Can be based on

And (4) determining. In some embodiments, the objective function is established based on a weighted sum of the first objective item, the second objective item, the third objective item, and the fourth objective itemAnd (4) counting. For example, the first target term is weighted more heavily than the second target term, which is weighted more heavily than the third target term, which is weighted more heavily than the fourth target term.

For example, the weights of the second target item, the third target item and the fourth target item are 1% of the previous weights in turn.

For example, the weight of the second target item is determined according to the number of warehouses responsible for allocation. The weight of the fourth target item is determined according to the number of the warehouse responsible for the allocation and the maximum value of the plurality of VLTs between the warehouse responsible for the allocation and the warehouse responsible for the allocation having the distribution relationship.

For example, the weighted second target term is based on

Determine, and pick>

Is negatively correlated with >>

Positively correlated->

Is set->

Number of elements in (1), W ₂ Is an adjustable parameter.

For example, the weighted fourth target term is according to W ₄ 、v _max 、

Determine, and pick>

Negative correlation with

Is positively correlated with v _max Negative correlation, W ₄ To be at leastThe parameters of the adjustment.

In step 120, an equalization model is built based on the equalization target. The equilibrium model comprises at least one decision variable related to warehouse delivery information, and the equilibrium model is used for configuring the warehouse delivery information.

In some embodiments, the first constraint is determined based on the inventory of the warehouse responsible for the allocation, the actual allocation, the minimum hold, the allocation demand, and whether the post-delivery inventory meets the minimum hold.

In some embodiments, the second constraint is determined based on the actual allocation of the warehouse responsible for allocation not exceeding the allocation demand.

In some embodiments, the third constraint is determined based on the actual allocation of the warehouse of the responsible allocator not exceeding the allocation demand.

In some embodiments, the fourth constraint is determined based on the contribution amount of the responsible warehouse to the responsible warehouse having the distribution relationship not exceeding the maximum value of the contribution demand amounts of all the responsible warehouses.

In some embodiments, the fifth constraint is determined based on whether a weighted sum of the allocation demands of all of the allocated warehouses, a weighted sum of the actual allocation quantities of all of the allocated warehouses, an equilibrium demand, and an allocation demand of all of the allocated warehouses are met. The balance demand includes the maximum of the weighted sum of the allocation demands of all the warehouses responsible for allocation and the weighted sum of the allocation demands of all the warehouses responsible for allocation.

In some embodiments, the sixth constraint is determined based on whether a weighted sum of the allocation demands of all of the warehouses responsible for allocation, a weighted sum of the actual allocation amounts of all of the warehouses responsible for allocation, the equilibrium demands, and the allocation demands of all of the warehouses responsible for allocation are met.

In some embodiments, the seventh constraint is determined according to whether the allocation demand of all the warehouses responsible for allocation is satisfied, and whether the allocation demand of all the warehouses responsible for allocation is satisfied.

In some embodiments, the equalization method may further include step 130.

In step 130, the distribution information for each warehouse is configured according to the equalization model.

In some embodiments, the equalization model is solved with the value of the minimized objective function as a solution objective to determine a value of at least one decision variable; and configuring the distribution information of each warehouse according to the value of at least one decision variable.

For example, the decision variables may include x _ij 、

y _ij 、

z ⁱⁿ 、z ^out At least one of (a).

In the above equalization model, the objective function may include 4 objective items, and different weights are given according to the importance degree of each objective item in the actual service scene. For example, what is preferably satisfied is the minimum reserve for each fitted bin; on the basis of meeting the minimum reserve, balancing the meeting rate of each allocation bin, and reducing the allocation times as much as possible; and finally, balancing the remaining inventory difference after the inventory is distributed by each distribution bin.

For example, among the constraints (s.t.) of the model, the first constraint gives the constraint that the fitted bin is related to its minimum hold after fitting into inventory. Since the solution objective of the equilibrium model is to find the minimum value, and

parameter item M of _s Is greater, so that the equalization model tries to make &'s in solution>

Take 0 to satisfy the minimum hold constraint for the allocation bin.

For example, the second and third constraints are used to constrain: the total dispense quantity of each dispensing bin cannot exceed the dispensable quantity (dispense demand) of that bin; the total loading of the individual loading bins cannot exceed the loading requirement of the loading bin.

For example, the fourth constraint is used to constrain: the amount of the dispense from the dispense bin i to the dispense bin j depends on whether the dispense bin i dispenses the dispense to the dispense bin j.

For example, the fifth, sixth, and seventh constraints are used to constrain: the total actual amount dispensed is equal to the total amount that can be dispensed, or equal to the total amount that can be dispensed.

For example, provision may also be made for constraints

And &>

The eighth and ninth constraints of the calculation method of (1).

Is fitted into a bin j ₁ And a loading bin j ₂ The absolute value of the gap of the satisfaction rate of the target inventory is balanced;

Is a dispensing bin i ₁ And a dispensing bin i ₂ The absolute value of the gap between the remaining stocks after the stock is dispensed.

For example, constraints for the domain in which each decision variable is given can also be set.

In some embodiments, the solution may be performed using a solver.

For example, decision variables of type 0-1 and integer are included in the equalization model; when the eighth and ninth constraints include absolute value terms, the eighth and ninth constraints may be linearized first.

For example, after the equalization model is linearized, the equalization model can be solved using a solver.

In view of the computation time problem of the http service call equalization model, the following embodiments include a heuristic algorithm of inventory equalization to obtain a higher quality solution with a larger problem size.

Fig. 2 shows a flow chart of some embodiments of step 130 of the present disclosure.

As shown in fig. 2, step 130 includes steps 210 to 230.

In step 210, an initial solution of the equalization model is solved using a greedy algorithm.

In some embodiments, the greedy algorithm includes the following steps.

In step 1, the minimum hold requirement is met.

In some embodiments, the decision variables are updated based on whether the total allocation is greater than or equal to the total allocation and whether there are allocation bins that do not meet the minimum hold size.

For example, the total amount of the ingredients are calculated; if the total blending quantity is larger than or equal to the total blending quantity, the requirement of the lowest holding quantity is met certainly, and the step 1 is finished; if the total allocation amount < total allocation amount, then a determination is made as to whether there is a allocation warehouse set with the quantity present < lowest holding quantity.

If the allocation warehouse set is an empty set, the minimum holding quantity requirement is met, and the step 1 is finished; if the allocation warehouse set is not an empty set, determining the current allocation bin according to the sequence of the allocation bin set for each allocation bin in the allocation warehouse set; determining the load from the distribution bin to the loading bin with the aim of meeting the minimum holding capacity, updating the decision variables (such as x) _ij 、y _ij ) Until the cycle is over.

In step 2, the entire demand is met.

In some embodiments, the decision variables are updated based on whether a dispensing bin exists in the set of dispensing bins that is capable of satisfying the dispensing needs of any dispensing bin on its own.

For example, for the allocation demand of the allocation bin, it is determined whether the allocation bin exists in the allocation bin set, and the allocation demand of the allocation bin can be completely (e.g. independently) satisfied; if so, the decision variables are updated based on the match bin and the match bin. For example, it is not considered in this step that the allocation requirement of an allocation bin needs to be satisfied by at least two allocation bins for distribution.

In step 3, the margin requirement is met.

For example, the allowable amount of the remaining allocation bin is configured to meet the allowable amount requirement of the remaining allocation bin until the allowable amount of the remaining allocation bin decreases to 0 or the allowable amount requirement of the remaining allocation bin decreases to 0, and the decision variable is updated according to the configuration result.

Therefore, by meeting the allocation requirement, the distribution integral quantity requirement and the allowance requirement, the allocation frequency between the bins can be effectively reduced, and the final target value is effectively reduced.

In step 220, the initial solution is adjusted according to the satisfaction of the allocation demand of each warehouse in charge of allocation in the initial solution.

For example, adjustments are made based on balancing the demand fulfillment rates of the matched bins. Table 1 gives the initial solutions obtained by the greedy algorithm.

TABLE 1

32 denotes that the loading amount from the loading bin 1 to the loading bin 2 is 32, and other values have the same meaning.

For example, the ratio of the current cargo quantity + the actual allocation quantity to the current cargo quantity + the demand allocation quantity of each warehouse is calculated; the ratios of the matched bins 2, 3, 4, 6 and 7 are 1, 0.35 and 1.125 respectively. The ratio indicates the rate of satisfaction of the requirements of the various warehouses, i.e. the allocation requirements of the allocation bins 2, 3 and 4 are all satisfied by 100%, and the requirement of the allocation bin 6 is only satisfied by 35%.

At this time, the matching requirements are unbalanced, and a part of the goods needs to be balanced from the warehouse with a high satisfaction rate to the warehouse with a low satisfaction rate. If the target value (i.e., the minimum value of the target function) improves (i.e., becomes smaller) after equalization, the decision variable is updated; the equalization is continued until the target value can no longer be improved.

In some embodiments, the initial solution is adjusted based on the VLT between the warehouse responsible for commit and the warehouse responsible for commit in the initial solution that has a delivery relationship.

The initial solution is adjusted, for example, by a variable neighborhood adjustment. The target value can be improved efficiently by the adjustment of the local solution (part of the initial solution) in the initial solution.

For example, table 2 gives the local solutions that the initial solution contains.

	Dispensing bin 2	Dispensing bin 3
			Dispensing bin 1	32	87
Dispensing bin 5	42	0

TABLE 2

It can be seen that the total dosage of the dispensing bin 1 to the dosing bin 2 and the dosing bin 3 is 119; the total dosage of the dispensing bin 5 to the dosing bin 2 and the dosing bin 3 is 42; the total blending amount of the blending bin 2 obtained from the blending bin 1 and the blending bin 5 is 74; the total amount of the ingredient taken from the dispensing bins 1 and 5 by the dispensing bin 3 is 87.

The local solutions in table 2 were adjusted, and the adjustment results are shown in table 3.

	Dispensing bin 2	Dispensing bin 3
			Dispensing bin 1	74	43
Dispensing bin 5	0	42

TABLE 3

It can be seen that before and after the adjustment, the total allocation demand and the allocation demand of the allocation bin and the allocation bin are not changed, but only the distribution line (distribution relationship) is changed. That is, the dispensing bin 5 is originally dispensed to the dispensing bin 2, and after adjustment, the dispensing bin 5 is dispensed to the dispensing bin 3. This adjustment may improve the target value if the VLT of dispense bin 5 to dose bin 3 is lower than the VLT of dispense bin 5 to dose bin 2. And effective distribution adjustment can be performed through circular traversal.

In step 230, a final solution of the equalization model is determined based on the adjustment results.

In some embodiments, the delivery relationship in the initial solution is adjusted; calculating whether the value of the target function of the equilibrium model is improved or not according to the adjustment result; and determining a final solution of the equilibrium model according to the adjustment result in the case of improvement. For example, the initial solution may be adjusted by swapping the dispense bin and the fit bin.

For exampleAt present, x _ij ＝20，y _ij =1,i as dispensing bin, j is dispensing bin; replacing the dispensing bin from the bin i to other dispensing bins, and calculating whether the target value is improved or not after the other dispensing bins are replaced; if the target value improves, the adjustment is recorded and the initial solution is updated.

For example, current x _ij ＝20，y _ij ＝1，x _mn ＝40，y _mn =1, indicating that the dispensing bin i is the loading bin j and the loading amount 20, and the dispensing bin m is the loading bin n and the loading amount 40; the distribution bin i is a distribution bin n with the distribution amount 40, and the distribution bin m is a distribution bin j with the distribution amount 20; calculating whether the target value is improved after exchanging the input bin and the output bin; if so, the adjustment is recorded and the initial solution is updated.

And comparing the optimal value obtained by solving the solver with the target value obtained by solving the heuristic algorithm, and comparing the solving time under the two methods, compared with the solving method of the solver.

In the aspect of solving speed, the solving time of a heuristic algorithm does not exceed 0.5s, and the solving time of a solver fluctuates greatly and is different from 0.1s to tens of seconds; in terms of the quality of the solution, the average value of gap obtained by randomly generating 100 arithmetic examples and comparing the arithmetic examples with gap = (heuristic algorithm target value-solver solution target value)/solver solution target value as a calculation formula is 7.4%.

The solution obtained by the heuristic algorithm is at least identical to the solution obtained by the solver, and in some cases, the gap =37%. Therefore, the heuristic algorithm can obtain a solution with higher quality in a shorter time and can become an alternative scheme of a model solving method under a large-scale condition.

Fig. 3 illustrates a schematic diagram of some embodiments of a delivery balancing method of a warehouse of the present disclosure.

As shown in fig. 3, the input data provided by the data input module includes VLT information and warehouse node information (e.g., warehouse code, inventory, allocation or discharge demand, forecasted sales, etc.) for different ODs (origin-destination). And based on the input data, carrying out equalization processing by using an algorithm module. In the model solving process of the algorithm module, two solving schemes are provided, namely solver solving and heuristic algorithm.

For example, in the model objective module, the objective items of the equalization model include 4 items, which are the penalty of the minimum hold not being met, the number of transfers between bins, the variance between bins after each allocated bin is allocated into stock (for characterizing the difference), and the variance between bins after each allocated bin is allocated into stock.

For example, the decision variables in the model decision variable module are used to indicate whether to make an equalization (i.e., a dispense) from bin i to bin j, the number of dispenses from bin i to bin j, and so on.

For example, in a heuristic algorithm, a greedy algorithm is firstly adopted to obtain an initial solution of inventory balance; and improving the initial solution so that the target value is close to the optimal value of the solver.

In the embodiment, the inventory balance optimization method aiming at the inter-bin allocation demand is constructed in consideration of the actual business scene demand; considering the problem of calculation time when the http service calls the algorithm, a corresponding heuristic method is further designed, the designed heuristic method has shorter solving time compared with a model solving method, and the average gap value between a target value obtained by the heuristic algorithm and an optimal value obtained by a solver is 7.4%.

The business scenario of inventory balancing is described below to clarify the balancing target of the warehouse.

In some embodiments, the equalization requirements of the warehouses are known. If the equilibrium demand of warehouse A is greater than 0, it means that the warehouse needs to be allocated with the cargo amount, and it is allocated with the warehouse. The allocation demand of allocation bin a is equal to its equilibrium demand.

If the equilibrium demand of warehouse A is less than 0, it indicates that the warehouse can dispense the amount of goods, and it is the dispensing bin. The dispensable amount (i.e., the dispense demand amount) of dispense bin a equals the negative equilibrium demand.

For example, table 4 shows the relevant information for each warehouse.

TABLE 4

From the equilibrium requirements for each warehouse in table 4, it can be determined: matching a warehousing set = { warehouse 2, warehouse 3, warehouse 4, warehouse 6, warehouse 7}; set of allocated bins = { bin 1, bin 5}.

In some embodiments, the cargo of warehouse 1 and warehouse 5 is allocated to warehouse 2, 3, 4, 6, 7 with a total allocation amount of 123+27=150 and a total allocation amount of 32+87+15+36+1= 171. 150< -171 demonstrate that the binning requirements cannot be fully met.

In this case, it is desirable to distribute the amount of goods as evenly as possible to the various dispensing bins. If it is now chosen to allocate quantities 32, 87, 0, 30, 1 to warehouses 2, 3, 4, 6, 7, respectively, the equalization target is not met. The causes of the imbalance include the following two points.

First, the demand of warehouse 4 is not considered, the allocation demand of warehouses 2, 3 is met by 100%, but the allocation demand of warehouse 4 is met by 0%, which is an unbalanced solution.

Secondly, according to the business requirements, the warehouse after the allocation of the allocation warehouse should not be lower than the minimum reservation amount required by the warehouse. Taking the warehouse 7 as an example, the allocation demand of the warehouse 7 is 1, the spot goods are 5, and the minimum holding amount is 8; after loading 1 unit of inventory, warehouse 7's spot stock =1+5=6, which is less than the minimum holding capacity requirement of the warehouse.

Thus, the proposed balancing scheme should firstly meet the minimum holding capacity requirements of the warehouse and secondly try to balance the distribution. On the basis, when the balance among the bins is carried out, two bins with smaller transportation advance periods are selected as much as possible for distribution, and meanwhile, the balance times among the bins are reduced as much as possible.

For example, when both warehouse A and warehouse B can be dispatched for warehouse C, warehouse A should be selected for warehouse C if the VLT of warehouse A to warehouse C is 4,B to warehouse C is 5. Because, the transport lead period from the A cabin to the C cabin is shorter.

The example given in table 4 is a scenario where total allocation demand > total allocation demand. When the total allocation demand is less than the total allocation demand, the allocation demands of all allocation bins can be met by 100%, and at the moment, the residual inventory difference after the inventory allocation of the allocation bins is required to be as close as possible, and the deviation cannot be too large.

In the above embodiment, based on the above described balance objective, an inventory balance optimization method for inter-bin allocation demand is provided. Firstly, a multi-target inventory balancing model is constructed by combining a specific inventory balancing service scene, and a solver is used for solving the constructed model; considering the requirement on the operation time of the algorithm by calling the balance model in an http service form, a heuristic algorithm for balancing among bins is further designed to improve the solving accuracy and the solving speed when the problem scale is increased.

Fig. 4 illustrates a block diagram of some embodiments of a distribution equalization apparatus of a warehouse of the present disclosure.

As shown in fig. 4, the distribution equalizing apparatus 4 of the warehouse includes: a determining unit 41, configured to determine, as a balance target, at least one of a requirement on a minimum holding amount of goods in the warehouse, a balance of delivery amounts between warehouses responsible for allocation, a minimum validity lead VLT of delivery, or a balance of delivery amounts between warehouses responsible for allocation; and the establishing unit 42 is configured to establish an equilibrium model according to the equilibrium target, where the equilibrium model includes at least one decision variable related to the warehouse delivery information, and the equilibrium model is used to configure the warehouse delivery information.

In some embodiments, the establishing unit 42 establishes an objective function of the equalization model based on at least one of whether a minimum hold of the goods in the plurality of warehouses is met, whether the warehouses responsible for allocation are equalized, whether the VLTs are equalized, or whether the warehouses responsible for allocation are equalized, the objective function including at least one decision variable.

In some embodiments, the equalizing device 4 further comprises: a solving unit 43, configured to solve the equilibrium model by using the value of the minimized objective function as a solving target to determine a value of at least one decision variable; and configuring the distribution information of each warehouse according to the value of at least one decision variable.

In some embodiments, the establishing unit 42 establishes the first target item according to whether the minimum holding amount of the goods in the plurality of warehouses is satisfied, establishes the second target item according to whether the warehouses responsible for allocation are balanced, establishes the third target item according to the VLT, and establishes the fourth target item according to whether the warehouses responsible for allocation are balanced; and establishing an objective function according to the weighted sum of the first objective item, the second objective item, the third objective item and the fourth objective item.

In some embodiments, the establishing unit 42 establishes the first target item according to the number of warehouses responsible for check-in, the inventory of which cannot meet the minimum holding amount after the goods are checked-in.

In some embodiments, the creation unit 42 creates the second target item based on a difference in satisfaction of the target inventory between the warehouses responsible for allocation after delivery.

In some embodiments, the establishing unit 42 determines the satisfaction condition of the target inventory according to the current cargo quantity, the distribution demand quantity and the actual distribution quantity of any warehouse in charge of distribution, wherein the satisfaction condition of the target inventory is negatively related to the sum of the current cargo quantity and the distribution demand quantity and positively related to the sum of the current cargo quantity and the actual distribution quantity.

In some embodiments, establishment unit 42 determines the third target item based on a plurality of VLTs between the warehouse responsible for the commit and the warehouse responsible for the commit having a distribution relationship.

In some embodiments, the establishing unit determines the third target item according to a difference between each VLT and a maximum value of the VLTs.

In some embodiments, the establishing unit 42 establishes the fourth target item according to a difference of the remaining inventory information between the warehouses responsible for dispensing after delivery.

In some embodiments, the establishing unit 42 determines the remaining inventory information according to the difference between the quantity of the present goods and the quantity of the dispensed goods of any one of the warehouses responsible for dispensing after delivery and the maximum value of the quantity of the present goods of all the warehouses responsible for dispensing, wherein the remaining inventory information is positively correlated with the difference between the quantity of the present goods and the quantity of the dispensed goods and is negatively correlated with the maximum value of the quantity of the present goods.

In some embodiments, the establishing unit 42 performs at least one of the following: determining a first constraint condition according to the current goods quantity, the actual distribution quantity, the minimum reserve quantity and the distribution demand quantity of a warehouse in charge of distribution and whether the delivered inventory quantity meets the minimum reserve quantity or not; determining a second constraint condition according to the fact that the actual dispensing amount of the warehouse in charge of dispensing does not exceed the dispensing demand amount; determining a third constraint condition according to the fact that the actual allocation amount of the warehouse in charge of the allocator does not exceed the allocation demand; determining a fourth constraint condition according to the fact that the allocation amount of the warehouse in charge of allocation with the distribution relation does not exceed the maximum value of the allocation demand of all warehouses in charge of allocation; determining a fifth constraint condition according to the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution, the weighted sum of the actual distribution quantities of all the warehouses responsible for distribution, the balance demand quantity and whether the distribution demand quantities of all the warehouses responsible for distribution meet or not, wherein the balance demand quantity comprises the maximum value of the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution and the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution; determining a sixth constraint condition according to whether the weighted sum of the allocation demand quantities of all the warehouses in charge of allocation, the weighted sum of the actual allocation quantities of all the warehouses in charge of allocation, the balanced demand quantity and the allocation demand quantities of all the warehouses in charge of allocation meet or not; or determining a seventh constraint condition according to whether the distribution demand of all warehouses in charge of distribution is met or not and whether the distribution demand of all warehouses in charge of distribution is met or not.

In some embodiments, the solving unit 43 solves the initial solution of the equalization model using a greedy algorithm; adjusting the initial solution according to the satisfying condition of the allocation demand of each warehouse in charge of allocation in the initial solution, or at least one item of VLT between the warehouse in charge of allocation and the warehouse in charge of allocation with a delivery relationship in the initial solution; and determining a final solution of the equilibrium model according to the adjustment result.

In some embodiments, the solving unit 43 adjusts the delivery relationship in the initial solution; calculating whether the value of the target function of the equilibrium model is improved or not according to the adjustment result; and determining a final solution of the equilibrium model according to the adjustment result in the case of improvement.

In some embodiments, the solving unit 43 performs the initial solution update according to whether the current total allocation amount is greater than or equal to the total allocation amount, and whether there is a warehouse in charge of allocation that does not satisfy the minimum holding amount; according to whether a warehouse in charge of allocation exists in the allocation bin set or not, the allocation requirement of one warehouse in charge of allocation can be met independently, and initial solution updating is continued; and utilizing the allowable amount of the rest warehouse in charge of allocation corresponding to the updated initial solution to meet the allocation amount requirement of the rest warehouse in charge of allocation until the allowable amount of the rest warehouse in charge of allocation is reduced to 0 or the allocation amount requirement of the rest warehouse in charge of allocation is reduced to 0, so as to continue the initial solution updating.

Fig. 5 illustrates a block diagram of further embodiments of a distribution equalization apparatus of a warehouse of the present disclosure.

As shown in fig. 5, the equalizing apparatus 5 of the warehouse of this embodiment includes: a memory 51 and a processor 52 coupled to the memory 51, the processor 52 being configured to execute a method for distribution balancing of a warehouse according to any one of the embodiments of the present disclosure based on instructions stored in the memory 51.

The memory 51 may include, for example, a system memory, a fixed nonvolatile storage medium, and the like. The system memory stores, for example, an operating system, an application program, a Boot Loader (Boot Loader), a database, and other programs.

As shown in fig. 6, the equalizing device 6 of the warehouse of this embodiment includes: a memory 610 and a processor 620 coupled to the memory 610, the processor 620 being configured to perform a method for warehouse distribution balancing in any of the embodiments described above based on instructions stored in the memory 610.

The memory 610 may include, for example, system memory, fixed non-volatile storage media, and the like. The system memory stores, for example, an operating system, an application program, a Boot Loader (Boot Loader), and other programs.

The equalization means 6 of the warehouse may also comprise an input output interface 630, a network interface 640, a storage interface 650, etc. These

interfaces

630, 640, 650 and the connections between the memory 610 and the processor 620 may be through a bus 660, for example. The input/output interface 630 provides a connection interface for input/output devices such as a display, a mouse, a keyboard, a touch screen, a microphone, and a sound box. The network interface 640 provides a connection interface for various networking devices. The storage interface 650 provides a connection interface for external storage devices such as an SD card and a usb disk.

As will be appreciated by one of skill in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

So far, a delivery balance method of a warehouse, a delivery balance apparatus of a warehouse, and a non-volatile computer-readable storage medium according to the present disclosure have been described in detail. Some details that are well known in the art have not been described in order to avoid obscuring the concepts of the present disclosure. Those skilled in the art can now fully appreciate how to implement the teachings disclosed herein, in view of the foregoing description.

The method and system of the present disclosure may be implemented in a number of ways. For example, the methods and systems of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the foregoing examples are for purposes of illustration only and are not intended to limit the scope of the present disclosure. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A distribution balancing method for a warehouse comprises the following steps:

establishing a balance model by taking at least one of the conditions of the lowest holding quantity of goods in the warehouse, the balance of delivery quantity among warehouses in charge of distribution, the minimum valid lead time VLT of delivery or the balance of delivery quantity among warehouses in charge of distribution as a balance target, wherein the balance model comprises at least one decision variable related to the delivery information of the warehouse and is used for configuring the delivery information of the warehouse.

2. The delivery balancing method according to claim 1, wherein the establishing a balancing model comprises:

establishing an objective function of the equalization model based on at least one of whether a minimum hold of goods in a plurality of warehouses is met, whether there is an equalization between warehouses responsible for allocation, a VLT, or whether there is an equalization between warehouses responsible for allocation, the objective function including the at least one decision variable.

3. The delivery balancing method of claim 2, wherein the establishing an objective function of the balancing model comprises:

establishing a first target item according to whether the minimum holding quantity of goods in the plurality of warehouses is met, establishing a second target item according to whether the warehouses responsible for allocation are balanced or not, establishing a third target item according to the VLT, and establishing a fourth target item according to whether the warehouses responsible for allocation are balanced or not;

establishing the objective function according to a weighted sum of the first objective item, the second objective item, the third objective item, and the fourth objective item.

4. The delivery balancing method of claim 3, wherein establishing the first target item based on whether the minimum holding amount of the goods in the plurality of warehouses is met comprises:

establishing the first target item according to the number of warehouses responsible for distribution, the warehouses of which the inventory cannot meet the minimum holding amount after the goods are distributed.

5. The delivery balancing method according to claim 3, wherein the establishing of the second target item according to whether the warehouses responsible for allocation are balanced or not comprises:

and establishing the second target item according to the difference of the satisfaction conditions of the target inventory among the warehouses which are responsible for distribution after distribution.

6. The delivery balancing method of claim 5, wherein the establishing the second target item comprises:

determining the satisfaction condition of the target inventory according to the current goods quantity, the distribution demand quantity and the actual distribution quantity of any warehouse in charge of distribution,

the satisfaction condition of the target inventory is inversely related to the sum of the present amount and the allocation demand amount, and positively related to the sum of the present amount and the actual allocation amount.

7. The delivery balancing method of claim 3, wherein the establishing the third target term according to the VLT comprises:

the third target item is determined based on a plurality of VLTs between the warehouse responsible for check-in and the warehouse responsible for check-out having a delivery relationship.

8. The delivery balancing method of claim 7, wherein the determining the third target item comprises:

determining the third target term according to a difference between each VLT and a maximum value of the VLTs.

9. The distribution balancing method according to claim 3, wherein the establishing of the fourth target item according to whether the warehouses responsible for distribution are balanced or not comprises the following steps:

and establishing the fourth target item according to the difference of the remaining inventory information among the warehouses in charge of distribution after distribution.

10. The delivery balancing method of claim 9, wherein the establishing the fourth target item comprises:

determining the remaining inventory information according to the difference between the current cargo quantity and the allocation quantity of any one warehouse in charge of allocation after distribution and the maximum value of the current cargo quantities of all warehouses in charge of allocation,

the remaining stock information is positively correlated with the difference between the present amount and the dispensed amount, and negatively correlated with the maximum value of the present amount.

11. The delivery balancing method of claim 3, wherein the first target term is weighted more heavily than the second target term, the second target term is weighted more heavily than the third target term, and the third target term is weighted more heavily than the fourth target term.

12. The delivery balancing method of claim 11, wherein the weight of the second target item is determined according to the number of warehouses responsible for check-in, and the weight of the fourth target item is determined according to the number of warehouses responsible for check-in and a maximum value of the VLTs between the warehouses responsible for check-in and the warehouses responsible for check-out having the delivery relationship.

13. The delivery balancing method of claim 1, wherein the establishing a balancing model comprises at least one of:

determining a first constraint condition according to the current goods quantity, the actual allocation quantity, the minimum reserve quantity, the allocation demand quantity of the warehouse in charge of allocation and whether the delivered inventory quantity meets the minimum reserve quantity or not;

determining a second constraint condition according to the fact that the actual dispensing amount of the warehouse in charge of dispensing does not exceed the dispensing demand amount;

determining a third constraint condition according to the fact that the actual allocation amount of the warehouse in charge of the allocator does not exceed the allocation demand;

determining a fourth constraint condition according to the fact that the allocation amount of the warehouse in charge of allocation with the distribution relation does not exceed the maximum value of the allocation demand of all warehouses in charge of allocation;

determining a fifth constraint condition according to the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution, the weighted sum of the actual distribution quantities of all the warehouses responsible for distribution, the balance demand quantity and whether the distribution demand quantities of all the warehouses responsible for distribution meet, wherein the balance demand quantity comprises the maximum value of the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution and the weighted sum of the distribution demand quantities of all the warehouses responsible for distribution;

determining a sixth constraint condition according to whether the weighted sum of the allocation demands of all the warehouses responsible for allocation, the weighted sum of the actual allocation quantities of all the warehouses responsible for allocation, the balanced demand and the allocation demands of all the warehouses responsible for allocation meet or not; or alternatively

And determining a seventh constraint condition according to whether the distribution demand of all warehouses in charge of distribution is met or not and whether the distribution demand of all warehouses in charge of distribution is met or not.

14. The delivery balancing method according to any one of claims 2 to 13, further comprising:

solving the equilibrium model with the value of the objective function minimized as a solution objective to determine the value of the at least one decision variable;

and configuring the warehouse delivery information according to the value of the at least one decision variable.

15. The delivery balancing method according to any one of claims 1 to 13, further comprising:

solving an initial solution of the equilibrium model by using a greedy algorithm;

adjusting the initial solution according to a meeting condition of allocation demand of each warehouse in charge of allocation in the initial solution, or at least one item of VLT between the warehouse in charge of allocation and the warehouse in charge of allocation with a delivery relation in the initial solution;

and determining a final solution of the equilibrium model according to the adjustment result.

16. The distribution balancing method of claim 15, wherein the adjusting the initial solution comprises:

adjusting the distribution relation in the initial solution;

calculating whether the value of the target function of the equilibrium model is improved or not according to the adjustment result;

and determining a final solution of the equilibrium model according to the adjustment result in the case of improvement.

17. The distribution balancing method of claim 15 wherein the solving an initial solution to the balancing model comprises:

performing initial solution updating according to whether the current total allocation amount is greater than or equal to the total allocation amount and whether a warehouse which is responsible for allocation and does not meet the minimum reserve capacity exists;

according to whether a warehouse in charge of allocation exists in the allocation bin set or not, the allocation requirement of one warehouse in charge of allocation can be met independently, and initial solution updating is continued;

and utilizing the allowable amount of the rest warehouse in charge of allocation corresponding to the updated initial solution to meet the allocation amount requirement of the rest warehouse in charge of allocation until the allowable amount of the rest warehouse in charge of allocation is reduced to 0 or the allocation amount requirement of the rest warehouse in charge of allocation is reduced to 0, so as to continue the initial solution updating.

18. A distribution equalization apparatus for a warehouse, comprising:

the determining unit is used for determining at least one of the requirement on the lowest holding quantity of goods in the warehouses, the balance of delivery quantity among the warehouses in charge of allocation, the minimum of the valid lead VLT of delivery or the balance of the delivery quantity among the warehouses in charge of allocation as a balance target;

and the establishing unit is used for establishing a balance model according to the balance target, the balance model comprises at least one decision variable related to the warehouse delivery information, and the balance model is used for configuring the warehouse delivery information.

19. A distribution equalization apparatus for a warehouse, comprising:

a memory; and

a processor coupled to the memory, the processor configured to perform the method of distribution balancing of a warehouse of any of claims 1-17 based on instructions stored in the memory.

20. A non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of delivery balancing of a warehouse as claimed in any one of claims 1 to 17.