CN117408608A - Digital warehouse management system and method thereof - Google Patents
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- 238000012384 transportation and delivery Methods 0.000 claims abstract description 141
- 238000003860 storage Methods 0.000 claims abstract description 93
- 238000007726 management method Methods 0.000 claims abstract description 42
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/06311—Scheduling, planning or task assignment for a person or group
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
- G06Q30/0635—Processing of requisition or of purchase orders
Abstract
The invention discloses a digital warehouse management system and a method thereof, which belong to the technical field of data processing, wherein the method comprises the following steps: acquiring a warehouse entry bill and extracting cargo information; calculating the relevance among the goods to be put in storage according to the order relevance, the demand relevance and the sales relevance among the goods to be put in storage; determining a plurality of core goods; determining storage positions of various goods to be stored; warehousing all the goods to be warehoused according to the determined storage positions; acquiring a delivery bill and extracting cargo information; calculating the importance degree of each delivery bill according to the order type, the order quantity, the emergency degree and the customer importance degree of each delivery bill, and taking the delivery bill with the highest importance degree as a target delivery bill; calculating the similarity between other delivery forms and the target delivery form; combining other delivery forms with the target delivery form to form a combined delivery form; and planning a picking path of the combined delivery bill, and picking and delivering the goods to be delivered in the combined delivery bill.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a digital warehouse management system and a method thereof.
Background
The digital warehouse can help enterprises to predict and plan inventory demands more accurately, avoid the problem of excessive or insufficient inventory, improve the efficiency, accuracy and sustainability of warehouse management, make the enterprises more competitive, meet customer demands and adapt to continuously changing market demands. Thus, digital warehouses have been rapidly developed.
The current digital warehouse management technology mainly utilizes RFID (radio frequency identification) chips to be attached to cargoes, so that the position and state of each cargoes can be tracked, the improvement of inventory management is facilitated, and inventory errors are reduced. The goods can be automatically recorded in the warehouse-in and warehouse-out processes, so that errors and delays of manual data input are reduced.
However, even if the RFID (radio frequency identification) chip technology is used, the position and state of each cargo can be tracked, various cargoes are put into storage only according to a preset plan in the process of putting in storage, and the cargoes are put out according to the order sequence in the process of putting out storage, so that the improvement of the cargo put in storage and put out storage efficiency is limited by using the RFID (radio frequency identification) chip technology, and a great improvement space is still provided in the aspects of cargo put in storage and put out storage efficiency.
Course of invention
In order to solve the technical problems that various cargoes are put in storage according to a preset plan and put out according to order sequence in the storage process, the improvement of the cargo storage and the put out efficiency is limited by utilizing an RFID (radio frequency identification) chip technology, and a large improvement space is still reserved in the aspects of cargo storage and the put out efficiency, the invention provides a digital warehouse management system and a digital warehouse management method.
First aspect
The invention provides a digital warehouse management method, which comprises the following steps:
s101: acquiring a warehouse entry list, and extracting cargo information of cargoes to be warehoused in each warehouse entry list;
s102: calculating the relevance among the goods to be put in storage according to the order relevance, the demand relevance and the sales relevance among the goods to be put in storage;
s103: determining a plurality of core cargos according to the relevance among the cargos to be put in storage;
s104: according to the turnover rate of each core cargo and the relevance between other non-core cargoes and the core cargoes, determining the storage position of each cargo to be put in storage;
s105: warehousing all the goods to be warehoused according to the determined storage positions;
s106: acquiring a delivery bill, and extracting cargo information of cargoes to be delivered in each delivery bill;
s107: calculating the importance degree of each delivery bill according to the order type, the order quantity, the emergency degree and the customer importance degree of each delivery bill, and taking the delivery bill with the highest importance degree as a target delivery bill;
s108: calculating the similarity between other delivery forms and the target delivery form;
s109: when the similarity between other delivery forms and the target delivery form is larger than the preset similarity, combining the other delivery forms with the target delivery form to form a combined delivery form;
s110: and planning a picking path of the combined delivery bill, and picking and delivering the goods to be delivered in the combined delivery bill according to the planned picking path.
Second aspect
The invention provides a digital warehouse management system, which comprises a processor and a memory for storing instructions executable by the processor; the processor is configured to invoke the instructions stored by the memory to perform the digitized warehouse management method of the first aspect.
Compared with the prior art, the invention has at least the following beneficial technical effects:
(1) According to the invention, the core goods are determined according to the relevance among the goods to be put in storage, so that the warehouse can pay attention to the goods important to the business better, and the core goods are placed at the position close to the warehouse outlet, thereby being beneficial to improving the management of the key inventory and ensuring the stability of the supply chain;
(2) According to the invention, the storage positions of the goods to be put in storage are automatically determined according to the turnover rate of each core goods and the relevance between other non-core goods and the core goods, so that the storage efficiency is further improved, the management efficiency of the warehouse is improved, and the goods with high turnover rate can be ensured to be easy to pick;
(3) According to the method and the system, the importance degree of each delivery order is calculated according to the order type, the order quantity, the emergency degree and the customer importance degree of each delivery order, the priority of the delivery order is determined, priority treatment of orders with higher importance degree is facilitated, delivery efficiency is further improved, and customer satisfaction is improved.
(4) And the delivery bill with the highest importance degree is taken as the target delivery bill, and other delivery bills with higher similarity degree are combined with the target delivery bill to form a combined delivery bill to be picked together, so that unnecessary repetition of a picking path is reduced, and the picking cost and time are reduced.
(5) According to the invention, the picking path planning is automatically carried out on the combined delivery bill, and the delivery of the goods to be delivered in the combined delivery bill can be picked according to the planned picking path, so that the delivery efficiency is further improved.
Drawings
The above features, technical features, advantages and implementation of the present invention will be further described in the following description of preferred embodiments with reference to the accompanying drawings in a clear and easily understood manner.
Fig. 1 is a schematic flow chart of a digital warehouse management method provided by the invention.
Fig. 2 is a schematic structural diagram of a warehouse-in method provided by the invention.
Fig. 3 is a schematic structural diagram of a method for delivering a warehouse according to the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will explain the specific embodiments of the present invention with reference to the accompanying drawings. It is evident that the drawings in the following description are only examples of the invention, from which other drawings and other embodiments can be obtained by a person skilled in the art without inventive effort.
For simplicity of the drawing, only the parts relevant to the invention are schematically shown in each drawing, and they do not represent the actual structure thereof as a product. Additionally, in order to simplify the drawing for ease of understanding, components having the same structure or function in some of the drawings are shown schematically with only one of them, or only one of them is labeled. Herein, "a" means not only "only this one" but also "more than one" case.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
In this context, it should be noted that the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected, unless otherwise explicitly stated and defined. Either mechanically or electrically. Can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
In addition, in the description of the present invention, the terms "first," "second," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Example 1
In one embodiment, referring to fig. 1 of the specification, a flow chart of a digital warehouse management method provided by the invention is shown. Referring to fig. 2 of the specification, a schematic structural diagram of a warehouse-in method provided by the invention is shown. Referring to fig. 3 of the specification, a schematic structural diagram of a method for delivering a warehouse provided by the invention is shown.
The invention provides a digital warehouse management method, which comprises the following steps:
s101: and acquiring the warehouse entry list, and extracting the goods information of the goods to be warehoused in each warehouse entry list.
Specifically, the cargo information of the cargo to be put in each put order may be extracted by Natural Language Processing (NLP) technology, optical Character Recognition (OCR) technology, or the like.
S102: and calculating the relevance among the goods to be put in storage according to the order relevance, the demand relevance and the sales relevance among the goods to be put in storage.
Wherein order relevance represents the co-occurrence frequency of different goods in a warehouse entry, i.e. the number of times they occur in the same order. The higher the frequency of items appearing in the same order, the stronger the order correlation between them.
Wherein demand relevance represents the common demand frequency between different goods in different orders, i.e. the number of times they are simultaneously demanded in different orders. The higher the frequency of common demands for goods, the stronger the demand correlation between them.
Wherein sales volume correlation represents the degree of correlation between sales volumes between different goods. If there is a similar trend in sales of two goods over a period of time, the sales correlation between them is high.
According to the method and the system, the order relevance, the demand relevance and the sales relevance among the goods to be put in storage are integrated, the relevance among the goods to be put in storage is calculated, and warehouse management can be more intelligent and efficient according to the relevance among the goods to be put in storage. These correlation analyses help to determine relationships between goods, thereby better meeting order requirements, reducing inventory and operating costs, and improving the efficiency and quality of inventory management.
In one possible implementation, S102 is specifically: calculating the relevance among the goods to be put in storage according to the following formula:
τ ij ＝α 1 ·τ 1 (i,j)+α 2 ·τ 2 (i,j)+α 3 ·τ 3 (i,j)
wherein τ ij Representing the relevance between the ith goods to be put in storage and the jth goods to be put in storage, and tau 1 (i, j) represents an order correlation between the ith and jth warehoused loads, α 1 Weights, τ, representing order relevance 2 (i, j) represents a demand correlation between the ith and jth warehoused loads, α 2 Weights, τ, representing demand relevance 3 (i, j) represents the sales association between the ith and jth warehoused loads, α 3 Weights representing sales associations.
Wherein, the person skilled in the art can set the weight alpha of the order relevance according to the actual situation 1 Weight of demand relevance alpha 2 Weight alpha associated with sales 3 The specific size of (3) is not limited in the present invention.
In one possible implementation, the order relevance is calculated by:
wherein τ 1 (i, j) represents an order correlation between the ith and jth warehoused loads, a) ij The number of times that the ith goods to be put in storage and the jth goods to be put in storage appear on the warehouse entry bill at the same time is represented, and a represents the total number of the warehouse entry bill.
In the invention, by analyzing the relevance of orders, goods with similar orders can be stored in similar positions, thereby reducing picking time and improving operation efficiency. This helps reduce the cost of transportation and handling between goods.
In one possible implementation, the requirement correlation is calculated by:
wherein τ 2 (i, j) represents a demand correlation between the ith and jth warehoused loads, b ij And b represents the total number of the warehouse-out list and the number of times that the ith and the jth warehoused goods are simultaneously appeared on the warehouse-out list.
In the present invention, demand relevance helps identify which items are typically demanded at the same time so that they can be deposited in easily accessible locations, reducing picking time and improving response time.
In one possible implementation, the sales correlation is calculated by:
wherein τ 3 (i, j) represents sales association between the ith and jth warehoused loads, c i Representing the sales of the ith goods to be put in storage, c j Indicating the sales of the ith goods to be put in storage.
In the invention, through sales correlation, you can better know which goods have high sales, so that it can be ensured that they are available at any time to meet the order in high demand.
Further, by better managing the goods related to orders, demand and sales, you can more quickly and accurately fulfill customer orders, improving customer service levels.
S103: and determining a plurality of core cargos according to the relevance among the cargos to be put in storage.
According to the invention, the core goods are determined according to the relevance among the goods to be put in storage, so that the warehouse can pay attention to the goods important to the business better, and the core goods are placed at the position close to the warehouse outlet, thereby being beneficial to improving the management of the key inventory and ensuring the stability of the supply chain.
In one possible implementation, S103 specifically includes sub-steps S1031 and S1032:
s1031: calculating the association strength of each cargo to be put in storage according to the following formula:
wherein sigma i Representing the association strength of the ith goods to be put in storage, tau ij The association between the ith and jth cargoes to be put in storage is represented, j=1, 2, …, n, n represents the total number of cargoes to be put in storage.
S1032: and arranging the goods to be put in storage according to the sequence of the association strength from high to low, and selecting a first preset number of goods to be put in storage with the front sequence as core goods.
The first preset number of sizes can be set by a person skilled in the art according to practical situations, and the invention is not limited. For example, the top 3 goods to be put in storage may be selected as core goods.
In the invention, the association strength of the goods to be put in storage is high, which means that the goods to be put in storage have strong association with other goods to be put in storage, more frequently occur in warehouse entry and warehouse exit, have better sales, and the goods to be put in storage with high association strength are determined as core goods, so that the core goods can be stored in a conspicuous position, are easy to identify and pick, reduce the risk of false delivery, and improve the accuracy of order processing. The method can help warehouse management to be more intelligent and efficient, improve operation efficiency, reduce cost and improve customer service quality. The key management of the core goods is beneficial to optimizing warehouse operation and improving the quality and efficiency of inventory management.
S104: and determining the storage position of each cargo to be put in storage according to the turnover rate of each core cargo and the relevance between other non-core cargoes and the core cargoes.
Wherein the turnover rate represents the rate at which goods in inventory are sold and replaced within a particular time period.
In one possible implementation, S104 specifically includes sub-steps S1041 and S1042:
s1041: constructing a position allocation objective function according to the turnover rate of each core cargo and the relevance of other non-core cargoes and the core cargoes:
wherein J is 1 () Represents a position allocation objective function, X represents a storage position, min () represents a minimum function, f i Represents the turnover rate of the ith core cargo, d i Represents the distance of the ith core cargo from the delivery port, β represents the weight of the core cargo item, i=1, 2, …, I represents the number of core cargoes, τ ij Representing the association between the ith core cargo and the jth cargo to be put in storage, d ij Representing the storage distance between the ith core shipment and the jth shipment to be stocked, 1-beta representing the weight of other non-core shipment items, j=1, 2, …, J i ，J i Representing the total number of other non-core shipments that have an association with the ith core shipment.
In the invention, the turnover rate of each core cargo is considered in the objective function, so that the core cargo with higher turnover rate can be placed at a position close to the delivery port, thereby being beneficial to accelerating the picking and delivery of the cargoes and improving the operation efficiency. The relevance of other non-core cargos and the core cargos is considered in the objective function, and the other non-core cargos can be placed near the core cargos which are relevant to the non-core cargos as much as possible, so that the picking time is reduced, and the ex-warehouse efficiency is further improved. At the same time, by depositing the relevant goods close to the core goods, the picking time can be reduced, since the picker can more easily operate in adjacent positions, reducing unnecessary movements.
The size of the weight β of the core cargo item can be set by a person skilled in the art according to actual situations, and the present invention is not limited thereto.
S1042: and solving the position distribution objective function by taking the minimum function value of the position distribution objective function as a target, and determining the storage position of each goods to be put in storage.
Specifically, the location allocation objective function may be solved by a genetic algorithm, a particle swarm optimization algorithm, an annealing algorithm, or the like.
In the invention, by constructing the position distribution objective function and carrying out the minimization solution, the optimal position distribution can be realized, so that the core goods and the related non-core goods are ensured to be stored in the most suitable positions, thereby being beneficial to improving the efficiency of inventory management and reducing the operation cost.
S105: and warehousing the goods to be warehoused according to the determined storage positions.
S106: and acquiring the delivery bill, and extracting the goods information of the goods to be delivered in each delivery bill.
Specifically, the goods information of the goods to be delivered in each delivery order may be extracted by Natural Language Processing (NLP) technology, optical Character Recognition (OCR) technology, or the like.
S107: and calculating the importance degree of each delivery bill according to the order type, the order quantity, the emergency degree and the customer importance degree of each delivery bill, and taking the delivery bill with the highest importance degree as the target delivery bill.
In the invention, taking the order with highest importance as the target order can ensure that the most critical order is processed first, which is helpful to improve the efficiency and accuracy of order processing.
In one possible implementation, S107 is specifically: calculating the importance degree of each ticket according to the following formula:
ρ i ＝η 1 ·c 1 +η 2 ·c 2 +η 3 ·c 3 +η 4 ·c 4
wherein ρ is i Represents the importance degree of the ith delivery order, c 1 Representing the order type, eta 1 Weights representing the order type, c 2 Representing the order quantity, eta 2 Weights representing the amount of order, c 3 Indicating the degree of emergency, eta 3 Weights indicating degree of urgency c 4 Represent the importance degree, eta of the customer 4 Weights indicating customer importance。
Wherein, the person skilled in the art can set the weight eta of the order type according to the actual situation 1 Weight η of order quantity 2 Weight η of degree of urgency 3 And the weight η of the customer importance level 4 The size of (3) is not limited in the present invention.
According to the method and the system, the importance degree of each delivery order is calculated according to the order type, the order quantity, the emergency degree and the customer importance degree of each delivery order, the priority of the delivery order is determined, priority treatment of orders with higher importance degree is facilitated, delivery efficiency is further improved, and customer satisfaction is improved.
S108: and calculating the similarity between other delivery forms and the target delivery form.
In particular, other delivery forms and products or goods involved in the target delivery form may be considered. They may be considered more similar if they contain similar products or goods.
In one possible implementation, S108 is specifically: calculating the similarity between other delivery forms and the target delivery form according to the following formula:
wherein ε j Representing the similarity of the j-th delivery bill and the target delivery bill, x ij Indicating whether the ith goods to be delivered in the target delivery form appear in the jth delivery form, if so, x ij =1, otherwise, x ij =0, i=1, 2, …, m, m representing the total number of goods to be delivered in the target delivery slip.
S109: when the similarity between other delivery forms and the target delivery form is larger than the preset similarity, combining the other delivery forms and the target delivery form together to form a combined delivery form.
In the invention, the delivery bill with highest importance degree is taken as the target delivery bill, and other delivery bills with higher similarity degree are combined with the target delivery bill to form a combined delivery bill for picking together, thereby being beneficial to reducing unnecessary repetition of picking paths and reducing picking cost and time.
S110: and planning a picking path of the combined delivery bill, and picking and delivering the goods to be delivered in the combined delivery bill according to the planned picking path.
Specifically, the location allocation objective function may be solved by a genetic algorithm, a particle swarm optimization algorithm, an annealing algorithm, or the like.
In one possible implementation, S110 specifically includes substeps S1101 to S1103:
s1101: constructing a picking path objective function by taking the shortest path of a picker as an objective:
wherein J is 2 () Represents a picking path objective function, Y represents a deposit location, min () represents a minimum function, E ij Indicating whether the ith goods to be delivered and the jth goods to be delivered in the combined delivery bill are adjacent or not, if so, E ij =1, otherwise, E ij ＝0，D ij Representing the distance between the ith goods to be delivered and the jth goods to be delivered in the combined delivery bill.
S1102: and solving the picking path objective function by taking the minimum function value of the picking path objective function as the objective, and determining the picking path of the combined delivery order.
S1103: and selecting and discharging the goods to be discharged in the combined discharging bill according to the planned selecting path.
In the invention, by constructing a picking path objective function, aiming at the shortest path of a picker, the picker can be ensured to take the shortest path when picking cargoes. This helps to reduce picking time and improve picking efficiency.
In one possible implementation, the present invention proposes a new and improved solution of genetic algorithm, and the substep S1102 specifically includes the grandchild steps S11021 to S11027:
s11021: initializing seedGroup, initial group Q 1 Each individual in the collection represents a sort of pick path that combines the outgoing sheets.
S11022: according to the initial population Q 1 The function value of each individual picking path objective function, the initial population Q is calculated 1 Fitness value of each individual:
wherein, delta (Y) i ) Indicating fitness value, z of the ith individual i Representing the intermediate fitness value, J, of the ith individual 2 (Y i ) The function value representing the picking path objective function of the i-th individual, k representing the scaling parameter, i=1, 2, …, n, n representing the total number of picking paths.
S11023: determining the probability of each individual being selected according to the fitness value of each individual:
wherein p (Y) i ) Representing the probability that the ith individual is selected.
S11024: randomly selecting individuals to be reserved according to the probability of each individual to be selected to form a population Q 2 。
In the invention, a probabilistic selection strategy is adopted, individuals are randomly selected to be reserved to form a new population, and poor individuals are allowed to be selected with a certain probability, which is helpful for maintaining diversity in the population. Preserving some worse individuals helps to avoid the population from prematurely sinking into the locally optimal solution, thereby better exploring the search space. This is because if the individual with the highest fitness is always selected, it may cause the algorithm to converge prematurely to a locally optimal solution, rather than a globally optimal solution. Probabilistic selection helps to slow down convergence speed, providing opportunities for more comprehensive searches.
S11025: for population Q 2 Performing crossover operation from population H 2 Two individuals are randomly selected as father body and mother body respectively to generate a random number, and the random number and the crossover probability p e Comparing the magnitudes, if the random number is smaller than the crossover probability p e Performing cross operation on the parent body and the parent body to generate new individuals so as to form a new population Q 3 The new individuals were generated as follows:
a second predetermined number of intermediate points are determined between the start and end points of the pick paths represented by the parents and the parents.
The second preset number of sizes can be set by a person skilled in the art according to practical situations, and the invention is not limited.
And randomly selecting a cross node in a rectangular range formed by the ith intermediate point of the father body and the ith intermediate point of the mother body.
And connecting the starting point, each intersection node and the end point to form a new path as a new individual.
In the invention, diversity is introduced by cross operation, the characteristics of different individuals are combined together, a new combination is created, and the maintenance of genetic algorithm and the increase of diversity of population are facilitated, so that the problem space is explored more comprehensively. Determining a plurality of intermediate points and then randomly selecting crossover nodes within a rectangular range helps introduce diversity. The path structure of the new individual can be completely different from that of the father, so that diversity in the population is increased, and the probability of finding the optimal path is improved.
S11026: for population Q 3 Performing mutation operation from population Q 3 Randomly selecting an individual as parent, generating a random number, and combining the random number with variation probability p m Comparing the size, if the random number is smaller than the variation probability p m Performing mutation operation on parent body to generate new individual to form new population Q 4 The new individuals were generated as follows:
a third predetermined number of intermediate points are determined between the start and end points of the pick path represented by the parent.
For the ith intermediate point of the father, calculating the straight line distance d from the ith intermediate point to the line between the (i-1) th intermediate point and the (i+1) th intermediate point i 。
At the ith intermediate point as the center of a circle, r is taken as the center i And randomly selecting a variation node in a circular range of the radius.
In the invention, local search can be realized by randomly selecting variant nodes and carrying out tiny changes of paths nearby the variant nodes, individuals with higher fitness are avoided from being destroyed, the paths are facilitated to be refined, and the solution is improved, especially under the condition of approaching to the optimal solution.
Wherein r is i ＝μ·d i Mu represents the coefficient of variation.
Alternatively, the coefficient of variation μmay be 1.5.
And connecting the starting point, each variation node and the end point to form a new path serving as a new individual.
In the invention, the mutation operation introduces new diversity, completely different path structures can be generated by adding or deleting intermediate points in the paths, the diversity of the population is increased, the escape of the local optimal solution and the more comprehensive searching of the problem space are facilitated, and the probability of finding the optimal path is improved.
S11027: repeating the steps, iterating until the preset iteration times are reached, and outputting a solution with the minimum fitness value as a picking path of the combined delivery bill.
According to the invention, the picking path planning is automatically carried out on the combined delivery bill, and the delivery of the goods to be delivered in the combined delivery bill can be picked according to the planned picking path, so that the delivery efficiency is further improved.
Compared with the prior art, the invention has at least the following beneficial technical effects:
(1) According to the invention, the core goods are determined according to the relevance among the goods to be put in storage, so that the warehouse can pay attention to the goods important to the business better, and the core goods are placed at the position close to the warehouse outlet, thereby being beneficial to improving the management of the key inventory and ensuring the stability of the supply chain.
(2) According to the invention, the storage positions of the goods to be put in storage are automatically determined according to the turnover rate of each core goods and the relevance between other non-core goods and the core goods, so that the storage efficiency is further improved, the management efficiency of the warehouse is improved, and the goods with high turnover rate can be ensured to be easy to pick.
(3) According to the method and the system, the importance degree of each delivery order is calculated according to the order type, the order quantity, the emergency degree and the customer importance degree of each delivery order, the priority of the delivery order is determined, priority treatment of orders with higher importance degree is facilitated, delivery efficiency is further improved, and customer satisfaction is improved.
(4) And the delivery bill with the highest importance degree is taken as the target delivery bill, and other delivery bills with higher similarity degree are combined with the target delivery bill to form a combined delivery bill to be picked together, so that unnecessary repetition of a picking path is reduced, and the picking cost and time are reduced.
(5) According to the invention, the picking path planning is automatically carried out on the combined delivery bill, and the delivery of the goods to be delivered in the combined delivery bill can be picked according to the planned picking path, so that the delivery efficiency is further improved.
Example 2
In one embodiment, the invention provides a digital warehouse management system comprising a processor and a memory for storing processor-executable instructions; the processor is configured to invoke the instructions stored by the memory to perform the digitized warehouse management method of embodiment 1.
The digital warehouse management system provided by the invention can realize the steps and effects of the digital warehouse management method in the embodiment 1, and in order to avoid repetition, the invention is not repeated.
Compared with the prior art, the invention has at least the following beneficial technical effects:
(1) According to the invention, the core goods are determined according to the relevance among the goods to be put in storage, so that the warehouse can pay attention to the goods important to the business better, and the core goods are placed at the position close to the warehouse outlet, thereby being beneficial to improving the management of the key inventory and ensuring the stability of the supply chain;
(2) According to the invention, the storage positions of the goods to be put in storage are automatically determined according to the turnover rate of each core goods and the relevance between other non-core goods and the core goods, so that the storage efficiency is further improved, the management efficiency of the warehouse is improved, and the goods with high turnover rate can be ensured to be easy to pick;
(3) According to the method and the system, the importance degree of each delivery order is calculated according to the order type, the order quantity, the emergency degree and the customer importance degree of each delivery order, the priority of the delivery order is determined, priority treatment of orders with higher importance degree is facilitated, delivery efficiency is further improved, and customer satisfaction is improved.
(4) And the delivery bill with the highest importance degree is taken as the target delivery bill, and other delivery bills with higher similarity degree are combined with the target delivery bill to form a combined delivery bill to be picked together, so that unnecessary repetition of a picking path is reduced, and the picking cost and time are reduced.
(5) According to the invention, the picking path planning is automatically carried out on the combined delivery bill, and the delivery of the goods to be delivered in the combined delivery bill can be picked according to the planned picking path, so that the delivery efficiency is further improved.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. A method of digital warehouse management, comprising:
s101: acquiring a warehouse entry list, and extracting cargo information of cargoes to be warehoused in each warehouse entry list;
s102: calculating the relevance among the goods to be put in storage according to the order relevance, the demand relevance and the sales relevance among the goods to be put in storage;
s103: determining a plurality of core cargos according to the relevance among the cargos to be put in storage;
s104: according to the turnover rate of each core cargo and the relevance between other non-core cargoes and the core cargoes, determining the storage position of each cargo to be put in storage;
s105: warehousing all the goods to be warehoused according to the determined storage positions;
s106: acquiring a delivery bill, and extracting cargo information of cargoes to be delivered in each delivery bill;
s107: calculating the importance degree of each delivery bill according to the order type, the order quantity, the emergency degree and the customer importance degree of each delivery bill, and taking the delivery bill with the highest importance degree as a target delivery bill;
s108: calculating the similarity between other delivery forms and the target delivery form;
s109: when the similarity between other delivery forms and the target delivery form is larger than the preset similarity, combining the other delivery forms with the target delivery form to form a combined delivery form;
s110: and planning a picking path of the combined delivery bill, and picking and delivering the goods to be delivered in the combined delivery bill according to the planned picking path.
2. The digitized warehouse management method according to claim 1, wherein S102 is specifically:
calculating the relevance among the goods to be put in storage according to the following formula:
τ ij ＝α 1 ·τ 1 (i,j)+α 2 ·τ 2 (i,j)+α 3 ·τ 3 (i,j)
wherein τ ij Representing the relevance between the ith goods to be put in storage and the jth goods to be put in storage, and tau 1 (i, j) represents an order correlation between the ith and jth warehoused loads, α 1 Weights, τ, representing order relevance 2 (i, j) represents a demand correlation between the ith and jth warehoused loads, α 2 Weights, τ, representing demand relevance 3 (i, j) represents the sales association between the ith and jth warehoused loads, α 3 Weights representing sales associations.
3. The digitized warehouse management method of claim 2, wherein the order relevance is calculated by:
wherein τ 1 (i, j) represents an order correlation between the ith and jth warehoused loads, a) ij The number of times that the ith goods to be put in storage and the jth goods to be put in storage appear on the warehouse entry bill at the same time is represented, and a represents the total number of the warehouse entry bill;
the calculation mode of the demand relevance is as follows:
wherein τ 2 (i, j) represents a demand correlation between the ith and jth warehoused loads, b ij The number of times that the ith goods to be put in storage and the jth goods to be put in storage appear on the warehouse-out bill simultaneously is represented, and b represents the total number of the warehouse-out bill;
the calculation mode of the sales volume relevance is as follows:
wherein τ 3 (i, j) represents sales association between the ith and jth warehoused loads, c i Representing the sales of the ith goods to be put in storage, c j Indicating the sales of the ith goods to be put in storage.
4. The digitized warehouse management method according to claim 1, wherein S103 specifically comprises:
s1031: calculating the association strength of each cargo to be put in storage according to the following formula:
wherein sigma i Representing the association strength of the ith goods to be put in storage, tau ij Representing the association between the ith goods to be put in storage and the jth goods to be put in storage, j=1, 2, …, n, n representing the total number of the goods to be put in storage;
s1032: and arranging the goods to be put in storage according to the sequence of the association strength from high to low, and selecting a first preset number of goods to be put in storage with the front sequence as the core goods.
5. The digitized warehouse management method according to claim 1, wherein S104 specifically comprises:
s1041: constructing a position allocation objective function according to the turnover rate of each core cargo and the relevance of other non-core cargoes and the core cargoes:
wherein J is 1 () Represents a position allocation objective function, X represents a storage position, and min () representsMinimum function, f i Represents the turnover rate of the ith core cargo, d i Represents the distance of the ith core cargo from the delivery port, β represents the weight of the core cargo item, i=1, 2, …, I represents the number of core cargoes, τ ij Representing the association between the ith core cargo and the jth cargo to be put in storage, d ij Representing the storage distance between the ith core shipment and the jth shipment to be stocked, 1-beta representing the weight of other non-core shipment items, j=1, 2, …, J i ，J i Representing a total number of other non-core goods that have an association with the ith core good;
s1042: and solving the position distribution objective function by taking the minimum function value of the position distribution objective function as a target, and determining the storage position of each goods to be put in storage.
6. The digitized warehouse management method of claim 1, wherein S107 is specifically:
calculating the importance degree of each ticket according to the following formula:
ρ i ＝η 1 ·c 1 +η 2 ·c 2 +η 3 ·c 3 +η 4 ·c 4
wherein ρ is i Represents the importance degree of the ith delivery order, c 1 Representing the order type, eta 1 Weights representing the order type, c 2 Representing the order quantity, eta 2 Weights representing the amount of order, c 3 Indicating the degree of emergency, eta 3 Weights indicating degree of urgency c 4 Represent the importance degree, eta of the customer 4 Weights indicating the importance of the customer.
7. The digitized warehouse management method according to claim 1, wherein S108 is specifically:
calculating the similarity between other delivery forms and the target delivery form according to the following formula:
wherein ε j Representing the similarity of the j-th delivery bill and the target delivery bill, x ij Indicating whether the ith goods to be delivered in the target delivery form appear in the jth delivery form, if so, x ij =1, otherwise, x ij =0, i=1, 2, …, m, m representing the total number of goods to be delivered in the target delivery slip.
8. The method for digitized warehouse management of claim 1, wherein S110 specifically comprises:
s1101: constructing a picking path objective function by taking the shortest path of a picker as an objective:
wherein J is 2 () Represents a picking path objective function, Y represents a deposit location, min () represents a minimum function, E ij Indicating whether the ith goods to be delivered and the jth goods to be delivered in the combined delivery bill are adjacent or not, if so, E ij =1, otherwise, E ij ＝0，D ij Representing the distance between the ith goods to be delivered and the jth goods to be delivered in the combined delivery bill;
s1102: solving the picking path objective function by taking the minimum function value of the picking path objective function as the objective, and determining the picking path of the combined delivery order;
s1103: and selecting and discharging the goods to be discharged in the combined discharging bill according to the planned selecting path.
9. The digitized warehouse management method of claim 8, wherein S1102 specifically comprises:
s11021: initializing a population, initial population Q 1 Each individual of the plurality representing a sort of pick path for the combined pick slip;
s11022: according to the initial population Q 1 The function value of each individual picking path objective function, the initial population Q is calculated 1 Fitness value of each individual:
wherein, delta (Y) i ) Indicating fitness value, z of the ith individual i Representing the intermediate fitness value, J, of the ith individual 2 (Y i ) A function value representing a picking path objective function of an i-th individual, k representing a scaling parameter, i=1, 2, …, n, n representing a total number of picking paths;
s11023: determining the probability of each individual being selected according to the fitness value of each individual:
wherein p (Y) i ) Representing the probability that the ith individual is selected;
s11024: randomly selecting individuals to be reserved according to the probability of each individual to be selected to form a population Q 2 ；
S11025: for population Q 2 Performing crossover operation from population H 2 Two individuals are randomly selected as father body and mother body respectively to generate a random number, and the random number and the crossover probability p e Comparing the magnitudes, if the random number is smaller than the crossover probability p e Performing cross operation on the parent body and the parent body to generate new individuals so as to form a new population Q 3 The new individuals were generated as follows:
determining a second preset number of intermediate points between the start point and the end point of the picking path represented by the parent body and the parent body;
randomly selecting a cross node in a rectangular range formed by the ith intermediate point of the father body and the ith intermediate point of the mother body;
connecting the starting point, each cross node and the end point to form a new path as a new individual;
s11026: for population Q 3 Performing mutation operation from population Q 3 Randomly selecting an individual as parent, generating a random number, and combining the random number with variation probability p m Comparing the size, if the random number is smaller than the variation probability p m Performing mutation operation on parent body to generate new individual to form new population Q 4 The new individuals were generated as follows:
determining a third preset number of intermediate points between the starting point and the end point of the picking path represented by the father;
for the ith intermediate point of the father, calculating the straight line distance d from the ith intermediate point to the line between the (i-1) th intermediate point and the (i+1) th intermediate point i ；
At the ith intermediate point as the center of a circle, r is taken as the center i Randomly selecting a variation node in a circular range of the radius;
wherein r is i ＝μ·d i Mu represents a coefficient of variation;
connecting the starting point, each variation node and the end point to form a new path as a new individual;
s11027: repeating the steps until the preset iteration times are reached, and outputting a solution with the minimum fitness value as a picking path of the combined delivery bill.
10. A digital warehouse management system comprising a processor and a memory for storing processor-executable instructions; the processor is configured to invoke the instructions stored in the memory to perform the digitized warehouse management method of any of claims 1 to 9.
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