Efficient goods picking method and system for warehouse

Abstract

The invention relates to the technical field of warehouse management, in particular to an efficient goods picking method and system for a warehouse. The invention provides an efficient goods picking system for a warehouse. The efficient goods picking system comprises a first order set output module, a full-load goods picking list output module, a second order set output module, a sub goods picking list output module and a display module. Through the arrangement of the first order set output module, the full-load picking order output module, the second order set output module, the sub-picking order output module and the display module, the full-load picking order and the sub-picking order are obtained according to the order information, the goods information and the genetic algorithm operation model, and the full-load picking order or the sub-picking order is displayed by the display terminal. And the effects of accurately picking the goods and improving the goods picking efficiency are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and particularly to a method and system for efficient picking in a warehouse. Background Art

[0002] Warehouse picking refers to the process of picking specified goods from a warehouse according to order requirements and sorting, packing, or labeling these goods. Picking is an important link in warehouse management, which not only ensures accurate picking without errors but also realizes efficient goods picking.

[0003] With the rapid development of e-commerce, current enterprises have increasingly strict requirements for order delivery time. Whether it is customers or enterprises, they hope that the delivery service is more perfect and efficient. Since the picking process accounts for most of the total logistics operations, optimizing the picking process is beneficial to improving the overall operation efficiency of logistics. However, the traditional picking method requires the picker to take a stack of picking lists, first look through them to understand roughly what goods need to be picked, and then find the locations of the goods in the warehouse. When there is a situation where a picking list needs to be picked multiple times, the traditional picking method is prone to missing picks or over-picking, which will result in a high error rate in picking and thus low picking efficiency. Summary of the Invention

[0004] In view of the above problems, the present application provides a method and system for efficient picking in a warehouse, which makes the goods picking in the warehouse more accurate and the picking efficiency higher.

[0005] As one aspect of the present application, there is provided a method for efficient picking in a warehouse, including: W1. Obtain order information, where the order information is the name of the goods and the quantity of each type of goods corresponding to the name of the goods; W2. Output a first order set based on the order information; W3. Obtain the corresponding goods information in the warehouse according to the order information, where the goods information includes the average weight of a single piece of goods, the average volume of a single piece of goods, and the location of the goods; W4. Take out several full-load picking lists from the first order set according to the average weight of a single piece of goods; W5. Take out the names of the goods in the first order set from which several full-load picking lists have been taken out, obtain the optimal path connecting these names of the goods according to the genetic algorithm operation model, and store it in the second order set; W6. Divide the second order set into several sub-picking lists according to the constraint conditions; W7. Pick goods according to the full-load picking lists and the sub-picking lists.

[0006] Optionally, outputting a first order set based on the order information specifically includes the following steps: Extract the product names from all order information of the current day, and count the total quantity of products corresponding to the product names; Store the product names and the corresponding total product quantities in the first order set in the form of a two-dimensional array. The first order set is , For the th product name, is the product name 's total product quantity, is the total number of product names in all orders; The average weight per single piece of goods corresponding to each product name is { }, For the th product name,

[0007] Optionally, the steps of taking out several full-load picking lists from the first order set according to the average weight per single piece of goods specifically include: T1. Assign as 1; T2. Judge whether " " holds. is the preset weight. If " " holds, go to T3; if " " does not hold, go to T4; T3. Output in the form of { } as a full-load picking list, and assign as , and return to T2; T4. Assign as , and judge whether " " holds. If " " holds, do nothing; if " " does not hold, return to T2.

[0008] Optionally, the second order set obtained according to the genetic algorithm operation model is , is the th product name in the second order set, is the product name 's corresponding total product quantity, is the total number of product names in the second order set.

[0009] Optionally, the steps of dividing the second order set into several sub-picking lists specifically include: S1. Obtain the sum of the total product quantities corresponding to all product names in the second order set, and denote it as ; S2. Judge whether " Whether "= 0" holds. If " = 0" holds, return S1; if " = 0" does not hold, then enter S3; S3. Assign i as 1; S4. Obtain the total weight data Q of the first i items in the order set, and determine whether "Q < " holds. If "Q < " holds, enter S5; if "Q < " does not hold, then enter S8; S5. Obtain the total volume data V1 of the first i items in the order set, and determine whether "V1 < V2" holds, where V2 is a preset volume. If "V1 < V2" holds, enter S6; if "V1 < V2" does not hold, then enter S8; S6. Determine whether "i = " holds. If "i = " holds, enter S8; if "i = " does not hold, then enter S7; S7. Assign i as i + 1, and return to S4; S8. Output the names of the first i - 1 items and the corresponding quantities of the items as a sub - picking list in the form of a two - dimensional array, delete the order information of these i - 1 item names in the second order set, and return to S1.

[0010] Optionally, the full - load picking list and the sub - picking list are output by a display terminal.

[0011] As another aspect of the present application, there is provided an efficient warehouse picking system, including: A first order set output module, configured to obtain order information and output a first order set based on the order information; A full - load picking list output module, configured to obtain goods information and output a full - load picking list according to the average weight of a single item; A second order set output module, configured to output a second order set according to a genetic algorithm operation model; A sub - picking list output module, configured to divide the second order set into several sub - picking lists according to constraint conditions.

[0012] Optionally, it further includes a display module for outputting the full - load picking list and the sub - picking list, and the display module includes a display terminal.

[0013] The present invention has the following advantages: Through the provided first order set output module, full-load picking list output module, second order set output module, sub-picking list output module and display module, the present invention obtains a full-load picking list and a sub-picking list according to order information, goods information and a genetic algorithm operation model, and displays a full-load picking list or a sub-picking list on a display terminal, achieving the effect of accurately picking goods and improving the picking efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following-described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0015] Figure 1 It is a schematic flowchart of a method for efficient picking in a warehouse in Embodiment 1 of the present invention.

[0016] Figure 2 It is a schematic structural diagram of a system for efficient picking in a warehouse in Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to make the objectives, technical solutions and advantages of the present application clearer, the following further details some embodiments of the present application in conjunction with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. However, those of ordinary skill in the art can understand that in various embodiments of the present application, many technical details are proposed to help readers better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions required to be protected by the present application can still be implemented.

[0018] Embodiment 1: Refer to Figure 1 , Embodiment 1 of the present invention provides a method for efficient picking in a warehouse, including: W1. Obtain order information; The order information is the name of the commodity and the quantity of each commodity corresponding to the name of the commodity; The order information is the relevant data of the customer order and provides important information required for the picking personnel to perform the picking operation.

[0019] W2. Output a first order set based on the order information; Specifically, it includes the following steps: Extract the names of the commodities in all order information of the day and count the total quantity of the commodities corresponding to the names of the commodities; Store the product name and the corresponding total quantity of the product in a two-dimensional array in the first order set. The first order set is , is the th product name, is the total quantity of the product ; is the total number of product names in all orders; The average weight per single piece of goods corresponding to each product name is { }, is the average weight per single piece of goods of the th product name; It should be added that, for example, the first order information of the day is: a1 pieces of product A, b1 pieces of product B, c1 pieces of product C, d1 pieces of product D, e1 pieces of product E; the second order information is: a2 pieces of product A, b2 pieces of product B, d2 pieces of product D, f1 pieces of product F; the third order information is: a3 pieces of product A, b3 pieces of product B, c2 pieces of product C, d3 pieces of product D, f2 pieces of product F; then the first order set is {(A, a1 + a2 + a3), (B, b1 + b2 + b3), (C, c1 + c2), (D, d1 + d2 + d3), (E, e1), (F, f1 + f2)}; Extract the product names in all order information of the day and count the total quantity of products corresponding to the product names. It is to weaken the concept of the same order, gather all orders together, and sum them up according to the product type category, which is convenient for subsequent operations and makes the picking process more perfect and efficient.

[0020] W3. Obtain the corresponding goods information in the warehouse according to the order information; The goods information includes the average weight per single piece of goods, the average volume per single piece of goods, and the goods location.

[0021] W4. Take out several full-load picking lists from the first order set according to the average weight per single piece of goods; The steps of taking out several full-load picking lists from the first order set according to the average weight per single piece of goods specifically include: T1. Assign a value to 1; T2. Judge whether " " holds. is the preset weight. If " " holds, enter T3; if " " does not hold, enter T4; T3. Output in the form of { } as a full-load picking list, assign a value to , and return to T2; T4. Assign a value For , determine whether " " holds. If " " holds, no operation is performed; if " " does not hold, return T2; For example, the product name has a total number of products of 100 pieces, and the average weight per piece of the product name is 2.3 kilograms, and the preset weight is 20 kilograms. Then, output a full-load picking list { , 8}, and at this time = 92; Then, output a full-load picking list { , 8}; and so on, the product name will output 12 full-load picking lists { , 8}, and finally the total number of products of the product name = 4; Or in another case, the product name has a total number of products of 5 pieces, and the average weight per piece of the product name is 0.5 kilograms, and the preset weight is 20 kilograms. does not hold, so the product name does not output a full-load picking list; It should be added that the weight carried by the picking truck has an upper limit. Take out several full-load picking lists from the first order set so that the picker can pick only one type of product on a single full-load picking list at a time. This method is to plan the types of products and then pick the same type of products with a large picking quantity. The main advantage is that only one item is picked at a time, saving the time of the picking process, having a shorter picking path, reducing the walking time of the picker, and improving the picking efficiency.

[0022] W5. Output the second order set; Take out the product names in the first order set from which several full-load picking lists have been taken out, obtain the optimal path connecting these product names according to the genetic algorithm operation model, and store them in the second order set; The second order set obtained according to the genetic algorithm operation model is , is the th product name in the second order set, is the product name corresponding total number of products,​​ is the total number of product names in the second order set; the genetic algorithm model is a very existing multi-objective optimization model, and the specific parameter settings and steps can be referred to the existing technology, which will not be elaborated here; In step W4, the full-load picking list in the first order set has been taken out. For the remaining goods, in order to save time, it is necessary to pick multiple kinds of goods at one time, so it is necessary to optimize the picking path to avoid multiple overlaps of the picking path and improve the picking efficiency; The genetic algorithm is a method that simulates the biological evolution mechanism to solve complex problems to obtain the optimal solution. Through mathematical means, the computer simulation operation is used to convert the problem-solving process into processes such as the crossover and mutation of chromosome genes in biological evolution; the genetic algorithm has a strong global search ability and can search for the optimal solution within the entire search space, rather than only searching locally; the search of the genetic algorithm is based on the population search. It will not stop searching because it finds a good solution, but continues to search for better solutions among other solutions, which ensures the diversity of the genetic algorithm in the process of searching for the optimal path and avoids falling into the local optimal solution. In the path optimization problem, the genetic algorithm can explore more possible paths and improve the quality of the solution.

[0023] W6. Divide the second order set into several sub-picking lists according to the constraint conditions; The steps of dividing the second order set into several sub-picking lists specifically include: S1. Obtain the sum of the total quantities of all product names in the second order set and denote it as ; S2. Judge whether " =0" holds. If " =0" holds, return to S1; if " =0" does not hold, then enter S3; S3. Assign the value of i as 1; S4. Obtain the total weight data Q of the first i products in the order set and judge whether "Q < " holds. If "Q < " holds, enter S5; if "Q < " does not hold, then enter S8; S5. Obtain the total volume data V1 of the first i products in the order set and judge whether "V1 < V2" holds. V2 is the preset volume. If "V1 < V2" holds, enter S6; if "V1 < V2" does not hold, then enter S8; S6. Judge whether "i = " holds. If "i = " holds, enter S8; if "i = " does not hold, then enter S7; S7. Assign i as i + 1 and return to S4; S8. Output the names of the first i - 1 items and their corresponding quantities as a two - dimensional array to form a sub - picking list, delete the order information of these i - 1 item names in the second order set, and return to S1; It should be added that if there are too many goods to be inspected on the picking list and the picker cannot pick all the goods at once, the picker will pick the same picking list multiple times. Multiple pickings of the same picking list will lead to a decrease in the picking accuracy rate. Therefore, the second order set needs to be divided into several sub - picking lists according to the constraint conditions so that the picker can pick a sub - picking list at once, achieving the purpose of improving the picking accuracy rate; Each sub - picking list stipulates the picking task for entering the warehouse at one time and needs to meet the constraint conditions simultaneously: the total weight of the picked goods does not exceed the preset weight, and the total volume does not exceed the preset volume.

[0024] W7. Pick goods according to the full - load picking list and the sub - picking list; The full - load picking list and the sub - picking list are output by the display terminal, and the display terminal is installed on the picking truck; There are many types of goods in the warehouse. If the picker picks goods with an ordinary picking list, the picker needs to be very familiar with the layout of the warehouse and the storage locations of the goods, and needs to know the types and quantities of goods stored on each shelf. However, even an old employee cannot completely remember the location of every good, let alone a new employee. If a large amount of time is spent looking for goods or errors occur, the picking efficiency will be reduced. Therefore, a display terminal is installed on the picking truck, and the layout of the warehouse and the locations of the goods on a full - load picking list or a sub - picking list in the warehouse will be displayed on the display terminal to facilitate the picker to quickly and accurately find the goods location.

[0025] Through the set first order set output module, full - load picking list output module, second order set output module, sub - picking list output module and display module, the present invention obtains the full - load picking list and the sub - picking list according to the order information, goods information and genetic algorithm operation model, and a full - load picking list or a sub - picking list is displayed by the display terminal, achieving the effect of accurately picking goods and improving the picking efficiency.

[0026] Embodiment 2: Refer to Figure 2 , the embodiment 2 of the present invention provides an efficient warehouse picking system, including: The first order set output module is used to obtain the order information and output the first order set based on the order information; The full - load picking list output module is used to obtain the goods information and output the full - load picking list according to the average weight of a single piece of goods; The second order set output module is used to output a second order set according to the genetic algorithm operation model; The sub-picking list output module is used to divide the second order set into several sub-picking lists according to the constraint conditions.

[0027] An efficient warehouse picking system further includes a display module for outputting full-load picking lists and sub-picking lists, and the display module includes a display terminal.

[0028] It should be understood that those of ordinary skill in the art can make improvements or transformations according to the above description, and all such improvements and transformations should fall within the protection scope of the appended claims of the present invention. The parts not described in detail in this specification belong to the prior art well-known to those skilled in the art.

Claims

1. A method for efficient warehouse picking, characterized in that: include: W1. Get order information, which includes the product name and the quantity of each product name. W2. Output a first order set based on the order information; W3. Obtain the corresponding cargo information in the warehouse according to the order information. The cargo information includes the average weight of a single cargo, the average volume of a single cargo, and the cargo location; W4. Take out several full-load picking lists from the first order set according to the average weight of a single piece of goods; W5, taking out the commodity names from the first order set from which several full-load picking lists have been taken out, obtaining the optimal path connecting these commodity names according to the genetic algorithm operation model, and storing them in the second order set; W6. Divide the second order set into several picking orders according to the constraint conditions; W7. Pick goods according to the full picking list and sub-picking list.

2. A method for efficient warehouse picking as claimed in claim 1, characterized in that: Outputting the first order set based on the order information specifically includes the following steps: Extract the product names from all order information on the day and count the total number of products corresponding to the product names; Store the product names and the corresponding total product quantities in the first order set in the form of a two-dimensional array. The first order set is , For the Product name, Product name The total number of products, The total number of product names in all orders; The average weight of each product is { }, For the The average weight of a single piece of goods for each product name.

3. The efficient warehouse picking method according to claim 1, characterized in that: The steps of taking out a number of full-load picking lists from the first order set according to the average weight of a single piece of goods specifically include: T1. Assignment is 1; T2, judgment "Is it established? is the preset weight, if " is established, enter T3; if " "Not true, go to T4; T3, with { } is output as a full-load picking list, and the assignment for , return to T2; T4. Assignment for ,judge" "Is it true? If" "Established, no operation; if" "Not true, return to T2.

4. The efficient warehouse picking method according to claim 1, characterized in that: The second order set obtained according to the genetic algorithm operation model is: , The second order set Product name, Product name The corresponding total number of goods, is the total number of product names in the second order set.

5. The efficient warehouse picking method according to claim 1, characterized in that: The steps of dividing the second order set into a plurality of picking lists specifically include: S1. Get the sum of the total number of goods corresponding to all the product names in the second order set and record it as ; S2. Judgment =0" is true, if " =0" is established, return to S1; if " =0” is not true, then go to S3; S3, assign i to 1; S4, obtain the total weight data Q of the first i items in the order set, and determine "Q< "Is it true? If "Q< " is established, go to S5; if "Q< "If it is not true, then go to S8; S5, obtain the total volume data V1 of the first i items in the order set, and determine whether "V1<V2" is true, V2 is the preset volume. If "V1<V2" is true, enter S6; if "V1<V2" is not true, enter S8; S6, judge "i= "Is it true? If "i= " is established, go to S8; if "i= ” is not true, then go to S7; S7, assign i to i+1, and return to S4; S8. Output the names of the first i-1 items and the corresponding quantities of the items in a two-dimensional array as a sub-picking list, delete the order information of the i-1 items in the second order set, and return to S1.

6. The efficient warehouse picking method and system according to claim 1, characterized in that: It also includes that the full-load picking list and the sub-picking list are output by the display terminal.

7. An efficient warehouse picking system, characterized in that: include: A first order set output module, used to obtain order information and output a first order set based on the order information; The full-load picking list output module is used to obtain cargo information and output the full-load picking list based on the average single-piece cargo weight; A second order set output module, used for outputting the second order set according to the genetic algorithm operation model; The sub-picking list output module is used to divide the second order set into a plurality of sub-picking lists according to the constraint conditions.

8. An efficient warehouse picking system, characterized in that: It also includes a display module for outputting a full-load picking list and a sub-picking list, and the display module includes a display terminal.

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