CN116050687A - Method, system, terminal and storage medium for picking up goods in manual warehouse - Google Patents

Method, system, terminal and storage medium for picking up goods in manual warehouse Download PDF

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CN116050687A
CN116050687A CN202310027634.5A CN202310027634A CN116050687A CN 116050687 A CN116050687 A CN 116050687A CN 202310027634 A CN202310027634 A CN 202310027634A CN 116050687 A CN116050687 A CN 116050687A
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picking
efficiency
goods
pickers
commodities
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CN116050687B (en
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余智
王庆东
赵久国
王瑾璠
郁志勇
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Hefei Chain Code Tengyun Information Technology Co ltd
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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
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • 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
    • G06Q10/00—Administration; Management
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Abstract

The invention discloses a method, a system, a terminal and a storage medium for picking up goods in an artificial warehouse, wherein the method comprises the following steps: acquiring a picking task, wherein the picking task comprises the required quantity of a plurality of commodities; acquiring the walking time of the warehouse positions between every two commodities; acquiring the respective corresponding searching efficiency of a plurality of picking workers; and determining the goods and the goods picking paths corresponding to the goods pickers respectively according to the required quantity of the goods, the walking time between every two goods and the searching efficiency of the goods pickers. According to the invention, the travelling time between commodity warehouse positions and the searching efficiency of different pickers are considered, so that commodities and picking paths which are responsible for all pickers are comprehensively determined, the finishing time of a picking task can be effectively shortened, and the overall picking efficiency is improved. Solves the problems of low overall picking efficiency, low human resource utilization rate and unfriendly to new people in the existing manual picking method.

Description

Method, system, terminal and storage medium for picking up goods in manual warehouse
Technical Field
The invention relates to the field of manual picking, in particular to a method, a system, a terminal and a storage medium for picking in a manual warehouse.
Background
The task of the pick method in the warehouse is to distribute a batch of orders to pickers reasonably and inform them of the pick path to reduce the pick time of the batch of orders. Briefly, the pick method consists essentially of two aspects: order allocation and pick path planning.
The prior art often considers pickers to be homogenous when designing a picking method, without distinguishing their capabilities. However, in practice, the picking efficiency of each worker varies greatly due to different experience and warehouse familiarity, and is particularly reflected in the goods searching aspect. If the pickers are considered to have the same capacity to find the goods during the picking process, then it is highly likely that complex picking tasks will be distributed to a "new person" that reduces the overall picking efficiency. Therefore, the existing manual picking method has the following problems:
the overall picking efficiency is low. The overall pick efficiency is manifested in the final completion time of one pick batch, i.e., the time of completion of the last pick. If the pickers are considered to have the same capacity to find the goods during the picking process, then complex picking tasks are likely to be dispatched to a "new person" thus reducing overall picking efficiency.
The resource utilization rate is not high. Because of the difference in picking efficiency of workers, experienced workers perform picking tasks faster, and "novice" often takes a significant amount of time. This allows the "old staff" to begin picking the next batch of goods most of the time after waiting for the "new" to complete during the picking of the same batch of orders, which results in the idling of some workers.
A certain working pressure is caused for a new person. Since "novice" is a bottleneck for picking each batch of orders, it is often the case that the next batch of orders is picked immediately after the completion of the picking of one batch of orders. This places a great psychological and physiological stress on the "novice" not only striking the enthusiasm of the staff, but also causing errors in the picking process.
Accordingly, there is a need for improvement and development in the art.
Disclosure of Invention
The invention aims to solve the technical problems that the prior art has low overall goods picking efficiency, low human resource utilization rate and unfriendly new people.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, an embodiment of the present invention provides a method for picking a good in an artificial warehouse, where the method includes:
acquiring a picking task, wherein the picking task comprises the required quantity of a plurality of commodities;
acquiring the walking time of the warehouse positions between every two commodities;
acquiring the respective corresponding searching efficiency of a plurality of picking workers;
and determining the commodity and the picking path corresponding to each picking worker respectively according to the required quantity of each commodity, the walking time between every two commodities and the searching efficiency of each picking worker.
In one embodiment, the method for determining the travel time of a warehouse location between two commodities includes:
acquiring a warehouse position distance between two commodities and a preset walking speed of a picking worker;
and determining the walking time of the stock position between the two commodities according to the quotient of the stock position distance and the walking speed.
In one embodiment, when the picker is a non-new person, the method for obtaining the searching efficiency of each non-new person includes:
acquiring the historical searching efficiency of the non-new person for the previous times;
and determining the finding efficiency of the non-new person according to the arithmetic average value of the historical finding efficiency of the previous times.
In one embodiment, when the pickers are new people, the method for acquiring the searching efficiency of each new person includes:
acquiring the first searching efficiency of all the non-new persons;
determining the find efficiency of each of the new people based on an arithmetic average of the first find efficiencies of all the non-new people.
In one embodiment, the determining the goods and the picking paths respectively corresponding to the pickers according to the required quantity of the goods, the walking time between the goods and the efficiency of the pickers includes:
constructing an optimization model according to the required quantity of the commodities, the walking time between every two commodities and the searching efficiency of the pickers, wherein an optimization target of the optimization model is that the completion time of the picking task is minimized;
and determining the commodity and the picking path respectively responsible for each picker according to the optimizing model.
In one embodiment, the optimization model is:
Figure BDA0004045804010000031
Figure BDA0004045804010000032
Figure BDA0004045804010000033
Figure BDA0004045804010000034
Figure BDA0004045804010000041
Figure BDA0004045804010000042
Figure BDA0004045804010000043
wherein i, j is a commodity number, which represents the i, j-th commodity, n= {1,2,., N } represents the present pick commodity set; t is t i Indicating the pick completion time for the ith item,
Figure BDA0004045804010000044
representing the maximum value of all commodity picking times; k represents the kth pickers, m= {1,2,., M } represents all pickers' sets; d, d i Representing the required quantity of the ith commodity; c ij Indicating a travel time from the ith commodity to the jth commodity; b k Representing the efficiency of the turn-over of the kth pickers; b is a constant; x is x ijk For decision variables, it is indicated that the kth picker picks item i first and then pick item j.
In one embodiment, the method further comprises:
acquiring the picking time, the walking time and the number of responsible commodities of each picking worker in the picking task;
determining the time length of the pick worker for finding in the pick task according to the difference value of the pick time length and the walking time length;
and determining the searching efficiency of the pickers in the picking task according to the difference value of the searching duration and the commodity quantity.
In a second aspect, an embodiment of the present invention further provides a picking system of an artificial warehouse, where the system includes:
the system comprises a to-be-picked item information processing module, a storage module and a storage module, wherein the to-be-picked item information processing module is used for acquiring a to-be-picked item task, and the to-be-picked item task comprises the required quantity of a plurality of commodities;
acquiring the walking time of the warehouse positions between every two commodities;
the worker searching efficiency statistics module is used for acquiring the searching efficiency corresponding to the plurality of picking workers respectively;
the decision module is used for determining the goods and the picking paths corresponding to the pickers respectively according to the required quantity of the goods, the walking time between every two goods and the searching efficiency of the pickers.
In a third aspect, an embodiment of the present invention further provides a terminal, where the terminal includes a memory and one or more processors; the memory stores more than one program; the program comprising instructions for performing a method of picking a good in a manual warehouse as described in any one of the above; the processor is configured to execute the program.
In a fourth aspect, embodiments of the present invention further provide a computer readable storage medium having stored thereon a plurality of instructions, wherein the instructions are adapted to be loaded and executed by a processor to implement the steps of the method of picking a good in any of the above-described manual warehouses.
The invention has the beneficial effects that: according to the embodiment of the invention, the travelling time between commodity warehouse positions and the searching efficiency of different pickers are considered, so that commodities and picking paths which are responsible for all pickers are comprehensively determined, the finishing time of a picking task can be effectively shortened, and the overall picking efficiency is improved. Solves the problems of low overall picking efficiency, low human resource utilization rate and unfriendly to new people in the existing manual picking method.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art.
Fig. 1 is a flow chart of a method for picking a good in an artificial warehouse according to an embodiment of the present invention.
Fig. 2 is a schematic block diagram of a picking system of an artificial warehouse according to an embodiment of the present invention.
Fig. 3 is a chart of a pick worker turn-over efficiency trend provided by an embodiment of the present invention.
Fig. 4 is a schematic block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
The invention discloses a method, a system, a terminal and a storage medium for picking goods in an artificial warehouse, which are used for making the purposes, the technical scheme and the effects of the invention clearer and more definite, and further detailed description of the invention is provided below by referring to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. The term "and/or" as used herein includes all or any element and all combination of one or more of the associated listed items.
It will be understood by those skilled in the art that all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs unless defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
In view of the above-mentioned drawbacks of the prior art, the present invention provides a method for picking a good in an artificial warehouse, the method comprising: acquiring a picking task, wherein the picking task comprises the required quantity of a plurality of commodities; acquiring the walking time of the warehouse positions between every two commodities; acquiring the respective corresponding searching efficiency of a plurality of picking workers; and determining the commodity and the picking path corresponding to each picking worker respectively according to the required quantity of each commodity, the walking time between every two commodities and the searching efficiency of each picking worker. According to the invention, the travelling time between commodity warehouse positions and the searching efficiency of different pickers are considered, so that commodities and picking paths which are responsible for all pickers are comprehensively determined, the finishing time of a picking task can be effectively shortened, and the overall picking efficiency is improved. Solves the problems of low overall picking efficiency, low human resource utilization rate and unfriendly to new people in the existing manual picking method.
As shown in fig. 1, the method includes:
step S100, acquiring a picking task, wherein the picking task comprises the required quantity of a plurality of commodities.
Specifically, the pick task mainly includes the type of merchandise currently required to be picked and the number required for each type of merchandise. For example, assuming that there are N commodities, the demand of the ith commodity is d i ,i＝1,2,...,N。
As shown in fig. 1, the method further includes:
step 200, obtaining the walking time of the warehouse positions between every two commodities.
Step S300, obtaining the respective corresponding searching efficiency of a plurality of picking workers.
Specifically, in this embodiment, it is required to calculate the walking time based on the distance between the stock positions of any two types of commodities in the picking task, and obtain the efficiency of searching for multiple pickers performing the picking task, so as to optimize the commodity distribution result and the picking path planning.
In one implementation, the method for determining the walking time of the warehouse location between two commodities includes:
step S201, acquiring a bin distance between two commodities and a preset walking speed of a picking worker;
and step S202, determining the walking time of the bin between two commodities according to the quotient of the bin distance and the walking speed.
Specifically, the present embodiment presets the walking speed of the pickers as a constant, and the walking time is calculated by dividing the bin distance between two types of goods by the walking speed. For example, the travel time of commodity i to commodity j is noted as c i,j ,i＝1,2,..,N,j＝1,2,...,N。
In one implementation, when the picker is a non-new person, the method for obtaining the searching efficiency of each non-new person includes:
step S301, obtaining the previous history searching efficiency of the non-new person for a plurality of times;
step S302, determining the searching efficiency of the non-new person according to the arithmetic average value of the historical searching efficiency of the previous times.
Specifically, the definition of the efficiency of the present embodiment is the average time required for the pickers to correctly find a good. The present embodiment classifies pickers into two categories, one category being non-new with work experience and the other category being new without work experience. For each non-new person, he stores a historical pick record, so that the historical turn-over efficiency of the non-new person several times before can be calculated based on the historical pick record. And taking the arithmetic average value of the historical searching efficiency of the previous times as the searching efficiency of the non-new person in the picking task.
For example, the non-new person k has a find efficiency of
Figure BDA0004045804010000081
wherein ,/>
Figure BDA0004045804010000082
Efficiency of the turn-over for the first 1 non-new person k,/->
Figure BDA0004045804010000083
The efficiency of the first 2 non-new people k and so on. Taking the arithmetic average of the previous q times of the searching efficiency of the non-new person k as the current searching efficiency.
In one implementation, when the pickers are new people, the method for acquiring the searching efficiency of each new person includes:
step S303, obtaining the first searching efficiency of all the non-new persons;
step S304, determining the searching efficiency of each new person according to the arithmetic average value of the first searching efficiency of all non-new persons.
Specifically, for each new person, the present embodiment uses the arithmetic average of the searching efficiency when all non-new persons pick up the goods for the first time as the searching efficiency in the current picking task of the new person.
As shown in fig. 1, the method further includes:
step 400, determining the goods and the picking paths corresponding to the pickers according to the required quantity of the goods, the walking time between every two goods and the searching efficiency of the pickers.
Specifically, the embodiment not only considers the required quantity of each commodity and the walking time among the commodity warehouse locations in decision making, but also considers the searching efficiency of different pickers in decision making, so that the searching efficiency plays a role in commodity distribution and commodity picking path planning. The goal of this embodiment is to minimize the time to complete the picking task, so that the non-new pick workers with a high final experience will be assigned more goods picking tasks, and the new pick workers will be assigned fewer goods picking tasks, so that the final picking efficiency of the two types of pick workers is equivalent, thereby optimizing the overall picking time, improving the utilization rate of the pick workers, and relieving the pressure of the new pick workers.
In one implementation, the step S400 specifically includes:
step S401, constructing an optimization model according to the required quantity of the commodities, the walking time between every two commodities and the finding efficiency of the pickers, wherein an optimization target of the optimization model is that the completion time of the picking task is minimized;
and step S402, determining the commodity and the picking path which are respectively responsible for each picker according to the optimization model.
Specifically, the optimization model in this embodiment is a typical mixed integer programming problem, and the optimization objective of the optimization model is to minimize the completion time of the current picking task, and the problem can be solved by using optimization solvers such as Gurobi, CPLEX, and the like. Finally, the goods and the goods picking paths (namely the goods picking sequence) corresponding to the goods picking workers are dispatched.
In one implementation, the optimization model is:
Figure BDA0004045804010000091
Figure BDA0004045804010000092
Figure BDA0004045804010000093
Figure BDA0004045804010000094
Figure BDA0004045804010000101
Figure BDA0004045804010000102
Figure BDA0004045804010000103
wherein i, j is a commodity number, which represents the i, j-th commodity, n= {1,2,., N } represents the present pick commodity set; t is t i Indicating the pick completion time for the ith item,
Figure BDA0004045804010000104
representing the maximum value of all commodity picking times; k represents the kth pickers, m= {1,2,., M } represents all pickers' sets; d, d i Representing the required quantity of the ith commodity; c ij Indicating a travel time from the ith commodity to the jth commodity; b k Representing the efficiency of the turn-over of the kth pickers; b is a constant; x is x ijk For decision variables, it is indicated that the kth picker picks item i first and then pick item j.
In one implementation, the method further comprises:
step S500, acquiring the picking time, the walking time and the number of responsible commodities of each picking worker in the picking task;
step S501, determining a time period for the pick worker to find in the pick task according to a difference between the pick time period and the travel time period;
step S502, determining the searching efficiency of the picker in the picking task according to the difference between the searching duration and the commodity number.
Specifically, after the current lot of picking tasks is completed, each picker needs to count his turn-over efficiency of the picking task. For example, the efficiency of the pick task is denoted as b' k ：
Figure BDA0004045804010000105
wherein ,yjk ＝∑ i∈N x ijk ∈{0,1"j ε N,1 indicates that item j was picked by picker k; 0 indicates that item j is not picked by picker k. b' k The first term of the numerator in the calculation formula of (1) represents the picking time of the picker k in the picking task at this time, and the second term represents the walking time of the picker k, so that the numerator represents the searching time of the picker k in picking; the denominator indicates the number of items that the picker is picking this time.
As shown in fig. 2, when a new person picks up goods, the efficiency of initially picking up goods is not high due to insufficient personal experience, low familiarity of a warehouse, etc., and large fluctuation (a large difference in pick efficiency between the front and rear times) occurs. Along with the accumulation of goods picking experience, goods picking workers are more familiar with warehouses, goods placement, paths and the like, and the efficiency of goods searching is gradually improved. The picking worker's efficiency of the picking process will eventually reach the bottleneck, no longer rise as a result of experience accumulation, and will thereafter be in a steady state.
The invention has the advantages that:
1. the resource diversity is considered, and the method is more in line with the actual situation. Specifically, the invention considers the turnover efficiency of workers in commodity distribution and commodity picking path planning decisions, is more practical, enables the decisions to be closer to the actual operation results, and updates the turnover efficiency of the workers after picking is finished each time.
2. The resource utilization rate is improved. According to the invention, commodities are reasonably distributed to different pickers according to the searching efficiency, so that the difference between the picking time and the running time of the different pickers in each picking task is small, and the utilization rate of the pickers is improved.
3. The picking pressure of new people is reduced. According to the invention, the simple order is distributed to the new person as much as possible in consideration of the searching efficiency of the worker, so that the new person can more easily pick up goods, the sudden state is dealt with, the picking efficiency of the goods picking worker is improved to a certain extent, and the working pressure of the new person is reduced.
Based on the above embodiment, the present invention further provides a picking system of an artificial warehouse, as shown in fig. 3, the system includes:
the information processing module 01 for picking goods is used for acquiring a picking task, wherein the picking task comprises the required quantity of a plurality of goods;
acquiring the walking time of the warehouse positions between every two commodities;
a worker searching efficiency statistics module 02, configured to obtain searching efficiencies corresponding to a plurality of pickers respectively;
the decision module 03 is configured to determine the goods and the picking paths corresponding to the pickers according to the required quantity of the goods, the walking time between every two goods, and the searching efficiency of the pickers.
In one implementation, the system further comprises:
and the picking task dispatch module 04 is used for dispatching the goods and the picking paths respectively corresponding to the pickers.
The key index statistics module 05 is used for acquiring the picking time length, the walking time length and the number of responsible commodities of each picking worker in the picking task;
determining the time length of the pick worker for finding in the pick task according to the difference value of the pick time length and the walking time length;
and determining the searching efficiency of the pickers in the picking task according to the difference value of the searching duration and the commodity quantity.
Based on the above embodiment, the present invention also provides a terminal, and a functional block diagram thereof may be shown in fig. 4. The terminal comprises a processor, a memory, a network interface and a display screen which are connected through a system bus. Wherein the processor of the terminal is adapted to provide computing and control capabilities. The memory of the terminal includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the terminal is used for communicating with an external terminal through a network connection. The computer program when executed by the processor implements a method of picking a good from a manual warehouse. The display screen of the terminal may be a liquid crystal display screen or an electronic ink display screen.
It will be appreciated by those skilled in the art that the functional block diagram shown in fig. 4 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the terminal to which the present inventive arrangements may be applied, and that a particular terminal may include more or less components than those shown, or may combine some of the components, or have a different arrangement of components.
In one implementation, the memory of the terminal has stored therein one or more programs, and the execution of the one or more programs by one or more processors includes instructions for performing a pick method of an artificial warehouse.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
In summary, the invention discloses a method, a system, a terminal and a storage medium for picking goods in an artificial warehouse, wherein the method comprises the following steps: acquiring a picking task, wherein the picking task comprises the required quantity of a plurality of commodities; acquiring the walking time of the warehouse positions between every two commodities; acquiring the respective corresponding searching efficiency of a plurality of picking workers; and determining the commodity and the picking path corresponding to each picking worker respectively according to the required quantity of each commodity, the walking time between every two commodities and the searching efficiency of each picking worker. According to the invention, the travelling time between commodity warehouse positions and the searching efficiency of different pickers are considered, so that commodities and picking paths which are responsible for all pickers are comprehensively determined, the finishing time of a picking task can be effectively shortened, and the overall picking efficiency is improved. Solves the problems of low overall picking efficiency, low human resource utilization rate and unfriendly to new people in the existing manual picking method.
It is to be understood that the invention is not limited in its application to the examples described above, but is capable of modification and variation in light of the above teachings by those skilled in the art, and that all such modifications and variations are intended to be included within the scope of the appended claims.

Claims (10)

1. A method of picking a good in an artificial warehouse, the method comprising:
acquiring a picking task, wherein the picking task comprises the required quantity of a plurality of commodities;
acquiring the walking time of the warehouse positions between every two commodities;
acquiring the respective corresponding searching efficiency of a plurality of picking workers;
and determining the commodity and the picking path corresponding to each picking worker respectively according to the required quantity of each commodity, the walking time between every two commodities and the searching efficiency of each picking worker.
2. The method of claim 1, wherein the method of determining the travel time of a bin between two of the items of merchandise comprises:
acquiring a warehouse position distance between two commodities and a preset walking speed of a picking worker;
and determining the walking time of the stock position between the two commodities according to the quotient of the stock position distance and the walking speed.
3. The method of claim 1, wherein when the picker is a non-new person, the method of obtaining the efficiency of the turn-over of each of the non-new persons comprises:
acquiring the historical searching efficiency of the non-new person for the previous times;
and determining the finding efficiency of the non-new person according to the arithmetic average value of the historical finding efficiency of the previous times.
4. A method of picking a person in a manual warehouse as claimed in claim 3, wherein when the pickers are new persons, the method of obtaining the efficiency of the turn-over for each of the new persons comprises:
acquiring the first searching efficiency of all the non-new persons;
determining the find efficiency of each of the new people based on an arithmetic average of the first find efficiencies of all the non-new people.
5. The method of claim 4, wherein determining the goods and the picking paths respectively corresponding to the pickers according to the required quantity of the goods, the travel time between the goods and the picking efficiency of the pickers comprises:
constructing an optimization model according to the required quantity of the commodities, the walking time between every two commodities and the searching efficiency of the pickers, wherein an optimization target of the optimization model is that the completion time of the picking task is minimized;
and determining the commodity and the picking path respectively responsible for each picker according to the optimizing model.
6. The method of picking a good for an artificial warehouse according to claim 5, wherein the optimization model is:
Figure FDA0004045802000000021
Figure FDA0004045802000000022
Figure FDA0004045802000000023
Figure FDA0004045802000000024
Figure FDA0004045802000000025
Figure FDA0004045802000000026
Figure FDA0004045802000000027
/>
wherein i, j is a commodity number, which represents the i, j-th commodity, n= {1,2,., N } represents the present pick commodity set; t is t i Indicating the pick completion time for the ith item,
Figure FDA0004045802000000028
representing the maximum value of all commodity picking times; k represents the kth pickers, m= {1,2,., M } represents all pickers' sets; d, d i Indicating the need for the ith commodityCalculating the number; c ij Indicating a travel time from the ith commodity to the jth commodity; b k Representing the efficiency of the turn-over of the kth pickers; b is a constant; x is x ijk For decision variables, it is indicated that the kth picker picks item i first and then pick item j.
7. The method of picking a good for an artificial warehouse of claim 1, further comprising:
acquiring the picking time, the walking time and the number of responsible commodities of each picking worker in the picking task;
determining the time length of the pick worker for finding in the pick task according to the difference value of the pick time length and the walking time length;
and determining the searching efficiency of the pickers in the picking task according to the difference value of the searching duration and the commodity quantity.
8. A system for picking a good in a manual warehouse, the system comprising:
the system comprises a to-be-picked item information processing module, a storage module and a storage module, wherein the to-be-picked item information processing module is used for acquiring a to-be-picked item task, and the to-be-picked item task comprises the required quantity of a plurality of commodities;
acquiring the walking time of the warehouse positions between every two commodities;
the worker searching efficiency statistics module is used for acquiring the searching efficiency corresponding to the plurality of picking workers respectively;
the decision module is used for determining the goods and the picking paths corresponding to the pickers respectively according to the required quantity of the goods, the walking time between every two goods and the searching efficiency of the pickers.
9. A terminal comprising a memory and one or more processors; the memory stores more than one program; the program comprising instructions for performing the method of picking of an artificial warehouse of any one of claims 1-7; the processor is configured to execute the program.
10. A computer readable storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to implement the steps of the method of picking a person warehouse as claimed in any one of claims 1 to 7.
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CN111415122A (en) * 2020-03-31 2020-07-14 北京京东振世信息技术有限公司 Goods picking method and goods picking system

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