CN111612196B - Method, device, equipment and storage medium for determining centralized replenishment path - Google Patents

Method, device, equipment and storage medium for determining centralized replenishment path Download PDF

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CN111612196B
CN111612196B CN201910137302.6A CN201910137302A CN111612196B CN 111612196 B CN111612196 B CN 111612196B CN 201910137302 A CN201910137302 A CN 201910137302A CN 111612196 B CN111612196 B CN 111612196B
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王弋宁
张颖芳
陈佳琦
王本玉
郭雨佳
金晶
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SF Technology Co Ltd
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Abstract

The application discloses a method, a device, equipment and a storage medium for determining a centralized replenishment path, wherein the method comprises the following steps: acquiring a concentrated replenishment task information set; acquiring a storage area coordinate set, a stock quantity unit information set and a picking area coordinate set from the centralized replenishment task information set; and inputting the storage area coordinate set, the stock quantity unit information set and the picking area coordinate set into a pre-established path optimization model, and outputting an optimal replenishment task path. The method for determining the concentrated replenishment path can improve the logistics operation efficiency during concentrated replenishment.

Description

Method, device, equipment and storage medium for determining centralized replenishment path
Technical Field
The invention relates to the technical field of logistics, in particular to a method, a device, equipment and a storage medium for determining a centralized replenishment path.
Background
With the development of electronic commerce, logistics plays an important role in electronic commerce. In the technical field of logistics, the cost of picking and replenishment accounts for more than 60% of the total cost of the distribution center, and the time spent on the picking and replenishment accounts for more than 35%. Therefore, optimizing the replenishment and picking paths, reducing the cost of operations becomes an important means for improving the efficiency of logistics operations.
In the prior art, the route related to the picking area in the picking process is optimized, and the route related to the storage area and the picking area in the replenishment process is replenished according to the traditional order of the goods position numbers, when the concentrated replenishment is needed, the efficiency of logistics operation is greatly reduced in the traditional mode.
Disclosure of Invention
In view of the foregoing drawbacks or shortcomings of the prior art, it is desirable to provide a method, apparatus, device, and storage medium for centralized restocking path determination.
In a first aspect, the present invention provides a method for determining a centralized replenishment path, including:
acquiring a concentrated replenishment task information set;
acquiring a storage area coordinate set, a stock quantity unit information set and a picking area coordinate set from the centralized replenishment task information set;
and inputting the storage area coordinate set, the stock quantity unit information set and the picking area coordinate set into a pre-established path optimization model, and outputting an optimal replenishment task path.
In one embodiment, a pre-established path optimization model includes:
establishing an objective function of time required by the concentrated replenishment task in the storage area and time required by the concentrated replenishment task in the sorting area;
and solving the objective function under the constraint condition set to obtain an optimal solution, wherein the optimal solution is an optimal replenishment task path.
In one embodiment, the set of constraints includes at least one of:
the commodity number, commodity weight and commodity volume of the concentrated replenishment task executed in the storage area are respectively smaller than or equal to the maximum commodity number, the maximum bearing and the maximum operation volume of the single replenishment task;
the concentrated replenishment tasks executed in the storage area are in one-to-one correspondence with the concentrated replenishment tasks of the sorting area;
task executors who execute the same centralized replenishment tasks in the storage area and the picking area are the same;
the first path and the second path required to perform the concentrated restocking task in the storage area and the sorting area satisfy the limit of the vending man problem TSP, respectively.
In one embodiment, the centralized replenishment task information set comprises: the object to be supplemented, a first coordinate corresponding to the object to be supplemented in the storage area, a second coordinate corresponding to the object to be supplemented in the picking area and attribute parameters of the object to be supplemented.
In one embodiment, the optimal restocking task path includes a first path that performs a concentrated restocking task at the storage area and a second path that performs a concentrated restocking task at the pick area.
In a second aspect, the present invention provides a concentrated restocking path determining device, including:
the first acquisition module is used for acquiring the concentrated replenishment task information set;
the second acquisition module is used for acquiring a storage area coordinate set, a stock quantity unit information set and a picking area coordinate set from the replenishment task information set;
the output module is used for inputting the storage area coordinate set, the stock quantity unit information set and the picking area coordinate set into a pre-established path optimization model and outputting an optimal replenishment task path.
In one embodiment, a pre-established path optimization model includes:
establishing an objective function of time required by the concentrated replenishment task in the storage area and time required by the concentrated replenishment task in the sorting area;
and solving the objective function under the constraint condition set to obtain an optimal solution, wherein the optimal solution is an optimal replenishment task path.
In one embodiment, the set of constraints includes at least one of:
the commodity number, commodity weight and commodity volume of the concentrated replenishment task executed in the storage area are respectively smaller than or equal to the maximum commodity number, the maximum bearing and the maximum operation volume of the single replenishment task;
the concentrated replenishment tasks executed in the storage area are in one-to-one correspondence with the concentrated replenishment tasks of the sorting area;
task executors who execute the same centralized replenishment tasks in the storage area and the picking area are the same;
the first path and the second path required to perform the concentrated restocking task in the storage area and the sorting area satisfy the limit of the vending man problem TSP, respectively.
In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements a method for determining a centralized replenishment path according to any one of the above when executing the computer program.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of determining a concentrated restocking path of any of the above.
According to the method, the device, the equipment and the storage medium for determining the concentrated replenishment path, the storage area coordinate set, the stock quantity unit information set and the picking area coordinate set are obtained according to the obtained concentrated replenishment task information set, then the storage area coordinate set, the stock quantity unit information set and the picking area coordinate set are input into a pre-established path optimization model, and the optimal replenishment task path is output from the model. In this embodiment, the centralized replenishment paths of the sorting area and the storage area are optimized at the same time, that is, the centralized replenishment paths of the sorting area and the storage area are minimized, so that the centralized replenishment time is saved, and the logistics operation efficiency during centralized replenishment is improved.
Further, the timeliness of the double-zone replenishment task is optimized by constructing the minimum objective function of the time required for the centralized replenishment tasks of the storage zone and the picking zone.
Further, the embodiment of the application constrains the control conditions such as the weight, the volume and the attribute of the object to be supplemented through the constraint condition set, so that the utilization rate of the logistics space of the storage area and the picking area is improved.
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Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the following drawings, in which:
FIG. 1 is a flow chart of a method for determining a centralized replenishment path according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a centralized replenishment path determining apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The present application is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the invention are shown in the drawings.
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
As mentioned in the background art, in the prior art, only the path of the picking area in the picking process is optimized, and the storage area and the replenishment process of the picking area are also carried out according to the conventional cargo space serial numbers, so that when the concentrated replenishment is required, the logistics operation efficiency is greatly reduced.
Therefore, it is desirable to provide a method for determining a concentrated replenishment path for improving the efficiency of concentrated replenishment.
Referring to FIG. 1, an exemplary flow chart of a method of centralized restocking path determination is shown, according to one embodiment of the present application.
As shown in fig. 1, in step 110, a centralized replenishment task information set is obtained.
Specifically, replenishment refers to transporting an object to be replenished from a shelf of a storage area to a shelf of a picking area corresponding to the object to be replenished. The object to be replenished is an item that is missing from the shelves of the sorting area and that is to be replenished from the shelves of the storage area. The objects to be supplemented can be various goods or commodities, for example, the objects to be supplemented can be classified according to the requirements and characteristics of consumers, such as clothes, foods, lives, uses and lines of consumers, including foods, clothes, shoes and caps, daily products, furniture, household appliances, textiles, hardware and electricity materials, kitchen ware and the like. Wherein the storage area comprises at least one shelf, each shelf further comprises at least one layer, and each layer has a plurality of storage spaces for storing goods. Likewise, the sorting area also includes at least one shelf, each shelf also including at least one tier, each tier also having a plurality of storage spaces for storing items.
The concentrated replenishment task is a replenishment task that is generated when the sorting area shelves are assumed to be all empty or most of the shelves are out of stock.
The concentrated replenishment task information set refers to an information set of objects to be replenished in a concentrated replenishment task.
In one embodiment, the centralized replenishment task information set may include: the object to be supplemented, a first coordinate corresponding to the object to be supplemented in the storage area, a second coordinate corresponding to the object to be supplemented in the picking area and attribute parameters of the object to be supplemented.
In this embodiment and the embodiments described below, each storage space of the storage area or the picking area is represented by one coordinate, and the coordinate may include three numerical values, for example, the coordinate may be represented by the number of storage spaces of the number of layers of the shelves, for example, the coordinate may be represented by (3, 2, 5) for the fifth storage space of the second layer of the third shelf.
In order to distinguish the coordinates of the storage area from the sorting area, in this and the embodiments described below, the first coordinates are used to represent the storage space on the respective shelf of the object to be replenished within the storage area. For example, the storage area is marked as an x area, and the first sitting mark corresponding to the storage space of the object to be supplemented on the corresponding shelf of the storage area is marked as x i Where i is the i-th object to be supplemented.
The second coordinates are used to represent the storage space of the object to be replenished on the corresponding shelf within the picking zone. For example, the picking zone is marked as zone y, and the second seat corresponding to the storage space of the object to be supplemented on the corresponding shelf of the picking zone is marked as zone y a Where a is the a-th object to be supplemented.
The attribute parameters of the object to be supplemented include the number, volume, weight, place of origin, etc. of the object to be supplemented, and it should be noted that the attribute parameters of the object to be supplemented are not limited to the foregoing.
In step 120, a storage area coordinate set, a stock quantity unit information set, and a picking area coordinate set are obtained from the centralized replenishment task information set.
Wherein the storage area coordinate set S 0 Is the set { x } of all the first coordinates in the storage area 1 ,…,x i ,…,x n I=1, …, n, n being the total number of first coordinates in the memory area.
Picking zone coordinate set S 1 Is the set { y } of all the second coordinates of the pick zone 1 ,…,y a ,…,y m Where a=1, …, m, m is the total number of second coordinates within the pickarea. The stock quantity unit information set is an information set of stock quantity units. The stock quantity units (Stock Keeping Unit, SKU), i.e., the base units for stock in and out metering, may be in units of parts, boxes, trays, etc. SKU is short for commodity unified numbering, and each product corresponds to a unique SKU number. For example, when any one of the attributes of a certain commodity such as a brand, a model, a configuration, a rank, a color, a packaging capacity, a unit, a date of production, a shelf life, a use, a price, a place of production, and the like is different from other commodities, the commodity is different from SKU numbers of other commodities.
In step 130, the storage area coordinate set, the stock quantity unit information set, and the picking area coordinate set are input into a pre-established path optimization model, and an optimal replenishment task path is output.
Specifically, the pre-established path optimization model can be used for obtaining the optimal replenishment task path by constructing the working time and the running path time of the storage area and the sorting area as target functions and solving the minimum value of the target functions by using the constraint condition set. I.e., to determine an optimal restocking task path for the task performer from a shelf of the storage area to a shelf of the pick area. Wherein the optimal restocking task path may include a first path to perform a concentrated restocking task at the storage area and a second path to perform a concentrated restocking task at the pick area.
The pre-established path optimization model can also output the shortest time corresponding to the optimal replenishment task path.
According to the method for determining the concentrated replenishment path, the storage area coordinate set, the stock quantity unit information set and the picking area coordinate set are obtained according to the obtained concentrated replenishment task information set, then the obtained storage area coordinate set, stock quantity unit information set and picking area coordinate set are input into a pre-established path optimization model, and the optimal replenishment task path is output from the model. In the embodiment of the application, the centralized replenishment paths of the storage area and the sorting area are simultaneously optimized through the path optimization model, so that the centralized replenishment time is saved, and the logistics operation efficiency during centralized replenishment is improved.
In one embodiment, the pre-established path optimization model may include:
establishing an objective function of time required by the concentrated replenishment task in the storage area and time required by the concentrated replenishment task in the sorting area;
and solving the objective function under the constraint condition set to obtain an optimal solution, wherein the optimal solution is an optimal replenishment task path.
The objective function of the time required by the concentrated replenishment task in the storage area and the time required by the concentrated replenishment task in the selection area can be established by summing the time required by the concentrated replenishment task in the storage area and the time required by the concentrated replenishment task in the selection area.
Wherein, the time required for the storage area to execute the centralized replenishment task can comprise: the time required for the executor to travel between the shelves corresponding to the first coordinates in the storage area, and the work time required for the executor to carry the objects to be replenished from the first coordinates corresponding to the storage area to the transport means. The transport means may be, for example, a carrier vehicle carrying the object to be replenished, a carrier robot, or the like.
The time required for an operator to travel between the shelves corresponding to the first coordinates in the storage area includes: in the concentrated replenishment process, the executor travels from one first coordinate i where the object to be replenished is placed to another first coordinate j where the object to be replenished is placed in the storage area for the sum of the travel time.
The operation time required for an operator to carry a plurality of objects to be replenished from the first coordinates corresponding to the objects to the transport means in the storage area includes: the executor carries the plurality of objects to be replenished from the first coordinates corresponding to the storage areas to the time sum of the operation time on the transport means. Wherein the time required to perform the concentrated restocking task at the pick zone may include: in the concentrated replenishment process, the time required for an operator to travel between shelves corresponding to the plurality of second coordinates in the picking area and the work time required for the operator to transport the plurality of objects to be replenished from the transport means to the second coordinates corresponding thereto in the picking area. The transport means may be, for example, a carrier carrying the object to be replenished, or a carrier robot or the like, and the time required for an operator to travel between shelves corresponding to the plurality of second coordinates in the picking zone includes: in the concentrated replenishment process, an operator walks from the second coordinate a of one object to be placed to the second coordinate b of the other object to be placed in the picking zone for a time sum of walking time.
The working time required for an operator to transport a plurality of objects to be replenished from a transport to a second coordinate corresponding thereto in the picking zone includes: the executor carries the plurality of objects to be replenished from the transport means to the corresponding second coordinates in the sorting area.
Let K be the set of executors, k= {1, …, p }, p being the number of executors, S 0 For the storage area coordinate set S 0 ＝{x 1 ,…,x n And n is the total number of the first coordinates. S is S 1 To pick zone coordinate set, S 1 ＝{y 1 ,…,y m And m is the total number of second coordinates. The kth actor (K e K) moves from the first coordinate i (i e S) 0 ) To another first coordinate j (j.epsilon.S 0 ) The required walking time is t ij . Actuator k includes x from first coordinate i to first coordinate j in the restocking path of the storage area ijk =1, otherwise, executor k does not include x from first coordinate i to first coordinate j in the restocking path of the storage area ijk =0, the sum of the walking times required by the storage area executor k is:
Figure BDA0001977331900000081
the operation time required by the executor k in the storage area to carry the object to be replenished from the first coordinate i to the transport means is gamma i The sum of the time of the operation time required by the storage area executor is: />
Figure BDA0001977331900000082
Actuator k moves from second coordinate a (a εS in the pick zone 1 ) To the second coordinate b (b E S 1 ) The required walking time is t ab Actuator k includes y from second coordinate a to second coordinate b in the pick zone restocking path abk =1, otherwise, actor k does not include y in the pick zone's restocking path from second coordinate a to second coordinate b abk =0, then the sum of the time of travel required by actor k in the pick zone is:
Figure BDA0001977331900000083
the operation time required by the executor k in the sorting area to convey the object to be replenished from the transport means to the second coordinate a corresponding to the object to be replenished in the sorting area is gamma a The sum of the time required for the operator to operate at the pick zone is then: />
Figure BDA0001977331900000084
When the centralized replenishment task is executed, the optimal replenishment path is determined by optimizing the running time consumed on the replenishment path and the operation time of the object to be replenished at each coordinate, and the path with the minimum sum of the required time is the optimal replenishment task path. In the embodiment of the application, by establishing that the minimum sum of the time required for executing the concentrated replenishment task in the storage area and the time required for executing the concentrated replenishment task in the sorting area is taken as the objective function, the method comprises the following steps:
Figure BDA0001977331900000085
the constraint condition set is used for constraining the objective function, so that the objective function can be solved under the constraint condition set to obtain an optimal solution, namely an optimal replenishment task path. The optimal solution is a solution which enables the objective function to reach the minimum value under the condition of meeting the constraint condition set. Optionally, when solving the objective function, a solver such as Cplex, gruobi and the like can be used for solving, and heuristic algorithms such as genetic algorithm, ACA (Ant Colony Algorithm ), tabu search, simulated annealing and the like can also be used for solving. The solution method is not limited here.
In this embodiment, a path optimization model is pre-established, an objective function of time required for executing a centralized replenishment task in a storage area and time required for executing the centralized replenishment task in a sorting area is first established, and then the objective function is solved under a constraint condition set to obtain an optimal solution, namely an optimal replenishment task path. In this embodiment, the optimal replenishment task path is obtained by solving the objective function constructed by the time required for executing the concentrated replenishment task in the storage area and the sorting area, and the time spent in executing the concentrated replenishment task is small, which means that the replenishment efficiency is higher when the executor completes the concentrated replenishment according to the corresponding path, thereby improving the logistics operation efficiency.
In one embodiment, the set of constraints includes at least one of:
the commodity number, commodity weight and commodity volume of the concentrated replenishment task executed in the storage area are respectively smaller than or equal to the maximum commodity number, the maximum bearing and the maximum operation volume of the single replenishment task;
the concentrated replenishment tasks executed in the storage area are in one-to-one correspondence with the concentrated replenishment tasks of the sorting area;
task executors who execute the same centralized replenishment tasks in the storage area and the picking area are the same;
the first path and the second path required to perform the concentrated restocking task in the storage area and the sorting area satisfy the limit of the vending man problem TSP, respectively.
Let K be the set of actors, k= {1, …, p }, p be the total number of actors, S 0 For the storage area coordinate set S 0 ＝{x 1 ,…,x n -wherein n is the first coordinateIs the sum of the first coordinates i (i e S) 0 ) The commodity quantity of the department replenishment is q i Each commodity weight is m i Each commodity volume is r i Actuator K (K e K) includes x from first coordinate i to first coordinate j in the restocking path of the storage area ijk =1, otherwise, executor k does not include x from first coordinate i to first coordinate j in the restocking path of the storage area ijk The maximum number of goods for the single replenishment task is Q, the maximum load of the single replenishment task is M, and the maximum operation volume of the single replenishment task is R, then the number of goods for the concentrated replenishment task in the storage area is equal to or less than the maximum number of goods for the single replenishment task, which is:
Figure BDA0001977331900000091
the commodity weight of the concentrated replenishment task executed in the storage area is less than or equal to the maximum bearing of the single replenishment task, and the maximum bearing is as follows:
Figure BDA0001977331900000092
the commodity volume for executing the concentrated replenishment task in the storage area is smaller than or equal to the maximum operation volume of the single replenishment task, and the maximum operation volume is as follows:
Figure BDA0001977331900000101
suppose S 1 To pick zone coordinate set, S 1 ＝{y 1 ,…,y m And m is the total number of second coordinates. The object to be supplemented for the operation of the executor k at the first coordinate i of the storage area is x ik In the second coordinate a (a.epsilon.S) 1 ) The object to be supplemented for the operation of the executor k is y ak The one-to-one correspondence between the concentrated replenishment tasks executed in the storage area and the concentrated replenishment tasks of the sorting area is:
Figure BDA0001977331900000102
suppose that task executor k includes x from first coordinate i to first coordinate j in the restocking path of the storage area ijk =1, where actor k includes y from second coordinate a to second coordinate b in the pick zone's restocking path abk =1, then the task executors that execute the same concentrated restocking task in the storage area and the pick area are the same:
Figure BDA0001977331900000103
and->
Figure BDA0001977331900000104
The sales and sales problem TSP is a minimum solution method in which the selected path is a path where there is no duplicate path among all paths. Suppose that actor k includes x from first coordinate i to first coordinate j in the restocking path of storage area ijk =1, executor k executes the t-th in the memory area 0 The coordinate set included in the replenishment path of each replenishment task is S t0 ，
Figure BDA0001977331900000107
S 0 Is the set of first coordinates of the memory area. Actuator k includes y from second coordinate a to second coordinate b in the pick zone restocking path abk =1, executor k executes the t in the pick zone 1 The coordinate set included in the replenishment path of each replenishment task is S t1 ，/>
Figure BDA0001977331900000108
S 1 For the second set of coordinates of the pick zone, the first and second paths required to perform the centralized replenishment task within the storage and pick zones satisfy the limit of the vending man problem TSP, respectively, as follows:
Figure BDA0001977331900000105
and->
Figure BDA0001977331900000106
In this embodiment, in the solving process, the constraint condition set is utilized to constrain the maximum load and the maximum volume of a single replenishment task in the centralized replenishment task, so that the replenishment task can be effectively arranged, the maximization of the space utilization rate of the storage area and the picking area is realized, and the optimal solution can be obtained further through the vending man problem in the constraint condition set on the basis of the constraint condition, and is used as the preferred result of the centralized replenishment task path.
Fig. 2 is a schematic structural diagram of a centralized replenishment path determining apparatus 200 according to an embodiment of the present invention. As shown in fig. 2, the apparatus may implement the method shown in fig. 1, and the apparatus may include:
a first obtaining module 210, configured to obtain a centralized replenishment task information set;
a second obtaining module 220, configured to obtain a storage area coordinate set, a stock quantity unit information set, and a picking area coordinate set from the replenishment task information set;
the output module 230 is configured to input the storage area coordinate set, the inventory unit information set, and the picking area coordinate set into a pre-established path optimization model, and output an optimal replenishment task path.
Optionally, the pre-established path optimization model includes:
establishing an objective function of time required by the concentrated replenishment task in the storage area and time required by the concentrated replenishment task in the sorting area;
and solving the objective function under the constraint condition set to obtain an optimal solution, wherein the optimal solution is an optimal replenishment task path.
Optionally, the constraint condition set includes at least one of:
the commodity number, commodity weight and commodity volume of the concentrated replenishment task executed in the storage area are respectively smaller than or equal to the maximum commodity number, the maximum bearing and the maximum operation volume of the single replenishment task;
the concentrated replenishment tasks executed in the storage area are in one-to-one correspondence with the concentrated replenishment tasks of the sorting area;
task executors who execute the same centralized replenishment tasks in the storage area and the picking area are the same;
the first path and the second path required to perform the concentrated restocking task in the storage area and the sorting area satisfy the limit of the vending man problem TSP, respectively.
Optionally, the centralized replenishment task information set includes: the object to be supplemented, a first coordinate corresponding to the object to be supplemented in the storage area, a second coordinate corresponding to the object to be supplemented in the picking area and attribute parameters of the object to be supplemented.
Optionally, the optimal restocking task path includes a first path to perform a concentrated restocking task at the storage area and a second path to perform a concentrated restocking task at the pick area.
The centralized replenishment path determining device provided in this embodiment may execute the embodiment of the method, and its implementation principle and technical effects are similar, and will not be described herein.
Fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present invention. As shown in fig. 3, a schematic diagram of a computer system 300 suitable for use in implementing a terminal device or server of an embodiment of the present application is shown.
As shown in fig. 3, the computer system 300 includes a Central Processing Unit (CPU) 301 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage section 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the system 300 are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. An input/output (I/O) interface 306 is also connected to bus 304.
The following components are connected to the I/O interface 305: an input section 306 including a keyboard, a mouse, and the like; an output portion 307 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 308 including a hard disk or the like; and a communication section 309 including a network interface card such as a LAN card, a modem, or the like. The communication section 309 performs communication processing via a network such as the internet. The driver 310 is also connected to the I/O interface 306 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 310 as needed, so that a computer program read therefrom is installed into the storage section 308 as needed.
In particular, according to embodiments of the present disclosure, the process described above with reference to fig. 1 may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the centralized replenishment path determination method described above. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 309, and/or installed from the removable medium 311.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present application may be implemented by software, or may be implemented by hardware. The described units or modules may also be provided in a processor. The names of these units or modules do not in some way constitute a limitation of the unit or module itself.
As another aspect, the present application also provides a computer-readable storage medium, which may be a computer-readable storage medium contained in the foregoing apparatus in the foregoing embodiment; or may be a computer-readable storage medium, alone, that is not assembled into a device. The computer-readable storage medium stores one or more programs for use by one or more processors in performing the centralized replenishment path determination method described herein.
The foregoing description is only of the preferred embodiments of the present application and is presented as a description of the principles of the technology being utilized. It will be appreciated by persons skilled in the art that the scope of the invention referred to in this application is not limited to the specific combinations of features described above, but also covers other technical solutions which may be formed by any combination of the features described above or their equivalents without departing from the inventive concept. Such as the above-described features and technical features having similar functions (but not limited to) disclosed in the present application are replaced with each other.

Claims (6)

1. A method for determining a concentrated restocking path, comprising:
acquiring a concentrated replenishment task information set;
acquiring a storage area coordinate set, a stock quantity unit information set and a picking area coordinate set from the centralized replenishment task information set;
inputting the storage area coordinate set, the stock quantity unit information set and the picking area coordinate set into a pre-established path optimization model, and outputting an optimal replenishment task path;
the pre-established path optimization model comprises:
establishing an objective function of time required for executing the concentrated replenishment task in the storage area and time required for executing the concentrated replenishment task in the picking area; the objective function is the sum of the time required by the concentrated replenishment task in the storage area and the time required by the concentrated replenishment task in the selection area;
solving the objective function under a constraint condition set to obtain an optimal solution, wherein the optimal solution is the optimal replenishment task path;
wherein the time required for executing the centralized replenishment task in the storage area comprises: the time required by an operator to travel between shelves corresponding to the first coordinates in the storage area and the operation time required by the operator to convey the objects to be supplemented from the first coordinates corresponding to the first coordinates to the transport means in the storage area;
the time required to perform the concentrated replenishment task within the picking zone includes: in the concentrated replenishment process, the time required by an operator to travel between shelves corresponding to the plurality of second coordinates in the picking zone and the operation time required by the operator to convey the plurality of objects to be replenished from the transport means to the second coordinates corresponding to the objects in the picking zone;
the set of constraints includes at least one of:
the commodity number, commodity weight and commodity volume of the concentrated replenishment task executed in the storage area are respectively smaller than or equal to the maximum commodity number, maximum bearing and maximum operation volume of the single replenishment task;
the concentrated replenishment tasks executed in the storage area are in one-to-one correspondence with the concentrated replenishment tasks of the sorting area;
task executors who execute the same centralized replenishment tasks in the storage area and the picking area are the same;
the first path and the second path required to perform the concentrated restocking task within the storage area and the picking area, respectively, satisfy the limit of the vending man problem TSP.
2. The method of claim 1, wherein the centralized restocking task information set comprises: the system comprises an object to be supplemented, a first coordinate corresponding to a storage area of the object to be supplemented, a second coordinate corresponding to a picking area of the object to be supplemented and attribute parameters of the object to be supplemented.
3. The method of claim 1, wherein the optimal restocking task path includes a first path to perform the concentrated restocking task at a storage area and a second path to perform the concentrated restocking task at a pick area.
4. A concentrated restocking path determining device, comprising:
the first acquisition module is used for acquiring the concentrated replenishment task information set;
the second acquisition module is used for acquiring a storage area coordinate set, a stock quantity unit information set and a picking area coordinate set from the replenishment task information set;
the output module is used for inputting the storage area coordinate set, the stock quantity unit information set and the picking area coordinate set into a pre-established path optimization model and outputting an optimal replenishment task path;
the pre-established path optimization model comprises:
establishing an objective function of time required for executing the concentrated replenishment task in the storage area and time required for executing the concentrated replenishment task in the picking area; the objective function is the sum of the time required by the concentrated replenishment task in the storage area and the time required by the concentrated replenishment task in the selection area;
solving the objective function under a constraint condition set to obtain an optimal solution, wherein the optimal solution is the optimal replenishment task path;
wherein the time required for executing the centralized replenishment task in the storage area comprises: the time required by an operator to travel between shelves corresponding to the first coordinates in the storage area and the operation time required by the operator to convey the objects to be supplemented from the first coordinates corresponding to the first coordinates to the transport means in the storage area;
the time required to perform the concentrated replenishment task within the picking zone includes: in the concentrated replenishment process, the time required by an operator to travel between shelves corresponding to the plurality of second coordinates in the picking zone and the operation time required by the operator to convey the plurality of objects to be replenished from the transport means to the second coordinates corresponding to the objects in the picking zone;
the set of constraints includes at least one of:
the commodity number, commodity weight and commodity volume of the concentrated replenishment task executed in the storage area are respectively smaller than or equal to the maximum commodity number, maximum bearing and maximum operation volume of the single replenishment task;
the concentrated replenishment tasks executed in the storage area are in one-to-one correspondence with the concentrated replenishment tasks of the sorting area;
task executors who execute the same centralized replenishment tasks in the storage area and the picking area are the same;
the first path and the second path required to perform the concentrated restocking task within the storage area and the picking area, respectively, satisfy the limit of the vending man problem TSP.
5. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the method of any of claims 1-3 when executing the computer program.
6. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method of any of claims 1-3.
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