CN111815019B - Production material storage method, device, equipment and readable storage medium - Google Patents
Production material storage method, device, equipment and readable storage medium Download PDFInfo
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Abstract
The invention provides a production material storage method, a production material storage device, production material storage equipment and a storage medium, wherein the method comprises the following steps: acquiring M production materials to be stored currently and N vacant positions on a shelf of a current warehouse; obtaining information of production materials placed at adjacent positions of each vacancy; based on the correlation between the production materials, the placement positions of the M production materials in the N vacant positions are calculated so that the sum of the correlations of the placed production materials with the production materials in the adjacent positions thereof is maximized. The storage system can store the production materials according to the correlation among the production materials, so that the production materials on the same delivery slip are positioned in the adjacent storage lattices of the goods shelf with higher probability, the condition that a user frequently moves among different goods shelves to extract different production materials when extracting the goods according to the delivery slip is avoided, and the extraction efficiency of the production materials is improved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a production material access management method, device, equipment and system.
Background
In the production process of electronic devices, materials (such as resistors, capacitors and the like) required for production are generally stored in shelves of a warehouse in a unified manner, and then when a delivery order is to be produced, corresponding workers manually select the materials from the corresponding shelves of the warehouse according to the materials required by the delivery order, and then transfer the materials to a corresponding workshop or a production line.
At present, when materials are stored on a shelf of a warehouse, the materials of the same type are generally placed together, and the materials of different types are randomly stored. It has the following disadvantages:
when the staff is taking the material according to the delivery list, sometimes a delivery list is provided with more types of materials, and at the moment, the staff may need to spend more time to move between the shelves which are far away in order to take the materials, so that the efficiency of taking the materials is low.
Disclosure of Invention
In view of this, the present invention provides a method, an apparatus, a device and a system for storing production materials, which can realize rapid extraction of the production materials.
The embodiment of the invention provides a production material storage method, which comprises the following steps:
acquiring M production materials to be stored currently and N vacant positions on a shelf of a current warehouse;
acquiring information of production materials placed at adjacent positions of each vacancy;
based on the correlation between the production materials, the placement positions of the M production materials in the N vacant positions are calculated so that the sum of the correlations of the placed production materials with the production materials in the adjacent positions thereof is maximized.
Preferably, the correlation between two production materials is used to indicate the probability that two production materials appear in the same delivery slip at the same time, and the higher the correlation is, the higher the probability that two production materials appear in the same delivery slip at the same time is.
Preferably, before calculating the placement positions of the M production materials in the N vacant positions based on the correlation between the production materials so that the sum of the correlation of the placed production materials with the production materials in the adjacent positions thereof is maximized, further comprising:
acquiring a plurality of historical delivery lists; wherein each historical delivery list comprises a plurality of production materials;
and calculating the correlation among the production materials according to the distribution condition of the production materials of each historical delivery list.
Preferably, the placement positions of the M production materials in the N empty positions are calculated based on the correlation between the production materials so that the sum of the correlation of the placed production materials with the production materials in the adjacent positions thereof is maximized, specifically:
acquiring all possible combination modes of placing the M production materials into the N vacant positions in a permutation and combination mode;
and calculating the sum of the correlations of each combination mode, and obtaining the combination mode with the maximum sum of the correlations to obtain the placement positions of the M production materials in the N vacant positions.
Preferably, the placement positions of the M production materials in the N empty positions are calculated based on the correlation between the production materials so that the sum of the correlation of the placed production materials with the production materials in the adjacent positions thereof is maximized, specifically:
and taking the sum of the correlations as a fitness function of a particle swarm algorithm, iteratively searching for an optimal correlation combination parameter through a particle swarm, and finding out the optimal M position arrangement from the N vacancies according to the optimal correlation combination parameter so as to obtain the placement positions of the M production materials in the N vacancies.
Preferably, the sum of the correlations is used as a fitness function of a particle swarm algorithm, an optimal correlation combination parameter is iteratively searched through a particle swarm, and an optimal M position arrangement is found from the N vacancies according to the optimal correlation combination parameter, so as to obtain the placement positions of the M production materials in the N vacancies, specifically comprising:
s1, initializing a particle swarm; the method comprises the steps of initializing and setting the number of populations, randomly setting M position arrangements, maximum evolution algebra and upper and lower limits of inertia weight; randomly initializing the position and speed of the search point, and setting the Pbest of each particle i (0) Calculating individual extreme value of the particle for the current position, recording the individual maximum value and the particle serial number of the whole population, and setting Nbest i (0) Is the current position of the largest particle;
s2, calculating each particleAnd comparing the fitness with the current individual extreme value of the particle to update the optimal position Pbest of each particle i (t), finding out the maximum value of the individual extreme values of all the particles to be compared with the current maximum value, if the maximum value exceeds the current maximum value, recording the serial number of the maximum particle, and updating the current position of the maximum particle to Nbest i (t)；
S3, updating the speed and the position of each particle;
s4, judging whether the current iteration number meets the maximum value T or not max Or whether the error is smaller than the minimum threshold value or not, if so, stopping iteration and outputting the optimal correlation combination parameter, otherwise, returning to the step S2;
s5: and finding out the optimal M position arrangements from the N empty positions according to the optimal correlation combination parameters.
Preferably, after calculating the placement positions of the M production materials in the N vacant positions based on the correlation between the production materials so that the sum of the correlations of the placed production materials with the production materials in the adjacent positions thereof is maximized, further comprising:
generating a vertex diagram comprising M +1 vertexes by taking the appointed point and the optimal M positions as vertexes; wherein the starting point of the vertex graph is the designated point;
and planning a path of the vertex diagram by adopting a Dijkstra algorithm to obtain a path with the shortest sum of distances from the specified point to other vertexes, so that a user can place the M production materials according to the shortest path.
An embodiment of the present invention further provides a production material storage device, including:
the vacancy acquisition unit is used for acquiring M production materials to be stored currently and N vacancies on a shelf of a current warehouse;
the adjacent information acquisition unit is used for acquiring the information of the production materials placed at the adjacent positions of each vacancy;
a placement position calculation unit for calculating placement positions of the M production materials in the N vacant positions based on correlations between the production materials so that a sum of correlations of the placed production materials with the production materials in the adjacent positions thereof is maximized.
The embodiment of the invention also provides production material storage equipment which comprises a memory and a processor, wherein a computer program is stored in the memory and can be executed by the processor so as to realize the production material storage method.
An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored, where the computer program can be executed by a processor of a device where the computer-readable storage medium is located, so as to implement the production material storage method described above.
In the embodiment, the production materials are stored according to the correlation among the production materials, so that the production materials on the same delivery list are located in the adjacent storage lattices of the shelves with a high probability, the situation that a user frequently moves among different shelves to extract different production materials when extracting the goods according to the delivery list is avoided, and the extraction efficiency of the production materials is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic flow chart of a production material storage method according to a first embodiment of the present invention.
FIG. 2 is a schematic diagram of a vertex diagram provided in a preferred embodiment of the present invention.
Fig. 3 (a) -3 (g) are schematic diagrams of a process for planning a path of a vertex graph by using Dijkstra algorithm.
Fig. 4 is a schematic structural view of a production material storage apparatus according to a second embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, a first embodiment of the present invention provides a production material storage method, which can be performed by production material storage equipment and at least includes:
s101, M production materials to be stored at present and N vacant positions on a shelf of a warehouse at present are obtained.
In this embodiment, the production materials are stored on a shelf in a warehouse, wherein the shelf has a plurality of storage cells, and the production materials can be placed in the storage cells.
In one embodiment, when the production materials are stored on the storage grid, a worker may sequentially scan the two-dimensional code on the production materials to be stored and the identification code (usually, the two-dimensional code) on the storage grid to be stored by using the handheld terminal, so as to bind the information of the production materials and the information of the storage grid.
In this embodiment, the production material storage device may be a computer device or an intelligent device such as a PDA, and the production material storage device stores information of storage cells of all shelves in the warehouse and production material storage information stored in correspondence to the storage cells, so that whether the storage cells store production materials and types of the production materials can be queried through the production material storage device. The information on the storage grid includes position information thereof, for example, a shelf to which the storage grid belongs, an arrangement in which the storage grid is located, and the like.
In this embodiment, when M new production materials need to be stored in the warehouse, the production material storage device first obtains M production materials to be currently stored and N empty spaces (i.e., storage boxes in which production materials are not stored) on the shelf of the current warehouse. In general, N is equal to or greater than M. If N is less than M, the current warehouse is slow down to produce materials, and a goods shelf needs to be added or part of the produce materials need to be cleaned.
S102, obtaining information of the production materials placed at the adjacent positions of each vacant position.
In this example, after obtaining N voids, information can be obtained on the production materials placed adjacent to each void. The adjacent positions may be four adjacent storage grids located at the upper, lower, left, and right of the same shelf as the empty space, and may further include storage grids corresponding to the empty space on the front shelf and the rear shelf of the shelf, and the like.
In this embodiment, the information of the production materials at least includes types of the production materials.
S103, calculating the placing positions of the M production materials in the N vacant positions according to the correlation among the production materials, so that the sum of the correlation between the placed production materials and the production materials at the adjacent positions is the maximum.
In this embodiment, the correlation between two production materials is used to indicate the probability that two production materials appear in the same delivery slip at the same time, and the higher the correlation is, the higher the probability that two production materials appear in the same delivery slip at the same time is.
In one implementation, the correlation between production materials may be obtained by:
acquiring a plurality of historical delivery lists; wherein each historical delivery list comprises a plurality of production materials;
and calculating the correlation among the production materials according to the distribution condition of the production materials of each historical delivery list.
For example, assume that there are currently 4 historical output sheets, which include production materials as shown in table 1:
TABLE 1
| Delivery note | A | | C | D | |
| 1 | ● | ● | ● | ||
| 2 | ● | ● | |||
| 3 | ● | ● | ● | ● | |
| 4 | ● | ● | ● |
Wherein, the black dots represent the production materials contained in the delivery bill. For example, the ex-warehouse slip 1 comprises production materials A, C and D. The ex-warehouse list 1 comprises production materials B and C, and so on.
After the historical delivery order is obtained, the correlation among the production materials can be obtained according to the historical delivery order. As shown in table 2:
TABLE 2
| Correlation | A | B | | D |
| A | ||||
| 1 | 2/4 | 3/4 | 2/4 | |
| |
2/4 | 1 | 3/4 | 2/4 |
| |
3/4 | 3/4 | 1 | 2/4 |
| |
2/4 | 2/4 | 2/4 | 1 |
Obviously, the higher the correlation, the greater the probability that two production materials will appear simultaneously in the same delivery slip.
In this embodiment, after obtaining the correlation of each production material, the storage space of each production material can be determined according to the correlation, and the placement principle is such that the sum of the correlations of the M production materials placed in the corresponding spaces and the production materials in the neighboring positions is the largest. The maximum sum of the correlations represents that the possibility that the material and the production material at the position adjacent to the material are in the same delivery order is the largest, so that when a user extracts the production material, the production material on the same delivery order is most probably obtained at the position adjacent to the material, and frequent movement among different shelves is avoided.
In summary, according to the production material storage method provided by this embodiment, the production materials are stored according to the correlation between the production materials, so that the production materials on the same delivery slip are located in the adjacent storage cells of the shelves with a high probability, thereby avoiding the situation that a user frequently moves between different shelves to extract different production materials when extracting goods according to the delivery slip, and improving the extraction efficiency of the production materials.
In order to facilitate an understanding of the invention, some preferred embodiments of the invention are described further below.
On the basis of the above-described embodiment, in a preferred embodiment of the present invention:
step S103 specifically includes:
acquiring all possible combination modes of placing the M production materials into the N vacant positions in a permutation and combination mode;
and calculating the sum of the correlations of each combination mode, and obtaining the combination mode with the maximum sum of the correlations to obtain the placement positions of the M production materials in the N vacant positions.
Wherein, according to the principle of permutation and combination, the M production materials are placed in the N vacant positions to have the total
And a combination mode, wherein the production material storage device acquires all combination modes, calculates the sum of the correlations in each combination mode, and acquires the combination mode with the maximum sum of the correlations, and the combination mode is the placement position of the M production materials in the N vacant positions.
On the basis of the above-described embodiment, in a preferred embodiment of the present invention:
step S103 specifically includes:
and taking the sum of the correlations as a fitness function of a particle swarm algorithm, iteratively searching for an optimal correlation combination parameter through a particle swarm, and finding out the optimal M position arrangement from the N vacancies according to the optimal correlation combination parameter so as to obtain the placement positions of the M production materials in the N vacancies.
When the values of M and N are large, a relatively large computer may be required by using a permutation and combination manner, so that the particle swarm PSO algorithm may be used in this embodiment to solve the optimal placement positions of the M production materials in the N vacant positions.
Specifically, it comprises the following steps:
s1, initializing a particle swarm; the method comprises the steps of initializing and setting the number of populations, randomly setting M position arrangements, maximum evolution algebra and upper and lower limits of inertia weight; randomly initializing the position and speed of the search point, and setting the Pbest of each particle i (0) Calculating individual extreme value of the particle for the current position, recording the individual maximum value and the particle serial number of the whole population, and setting Nbest i (0) The current position of the largest particle.
Wherein, in an N-dimensional (corresponding to N empty spaces) target search space, M particles (corresponding to M production materials) form a population, and the population can be represented as X = { X = { (X) } 1 ,L,x i ,L,x M }。
S2, calculating the fitness of each particle, comparing the fitness with the current individual extreme value of the particle, and updating the optimal position Pbest of each particle i (t), finding out the maximum value of the individual extreme values of all the particles to be compared with the current maximum value, if the maximum value exceeds the current maximum value, recording the serial number of the maximum particle, and updating the current position of the maximum particle to Nbest i (t)。
And S3, updating the speed and the position of each particle.
Wherein, at time t, the position and speed of the ith particle are respectively represented by vector x i (t)＝(x i1 ,x i2 ,L,x iN ) T And v i (t)＝(v i1 ,v i2 ,L,v iN ) T Express, pbest i (t)＝(Pbest i1 ,Pbest i2 ,L,Pbest iN ) T And Nbest i (t)＝(Nbest i1 ,Nbest i2 ,L,Nbest iN ) T Respectively representing the optimal position searched by the ith particle and the optimal position searched by the whole population. Particle x i The updating mode of the speed and the position is as follows:
in the formula, r 1 And r 2 Is uniformly distributed in [0,1 ]]A random number between c 1 And c 2 Are learning factors, which are usually taken as 2; w is the inertial weight, and the calculation formula is as follows:
in the formula, w max ,w min Respectively representing the upper and lower limits of the inertial weight, T max Is the maximum evolution algebra.
S4, judging whether the current iteration number meets the maximum value T or not max Or whether the error is smaller than the minimum threshold value or not, if so, stopping iteration and outputting the optimal correlation combination parameter, otherwise, returning to the step S2;
s5: and finding out the optimal M position arrangements from the N vacant positions according to the optimal correlation combination parameters.
In the embodiment, the optimal placement position of each production material is calculated by adopting a particle swarm algorithm, so that the calculation efficiency is higher under the condition that the numerical values of M and N are larger.
On the basis of the above-described embodiment, in a preferred embodiment of the present invention: after calculating placement positions of the M production materials in the N vacant positions based on the correlation between the production materials so that the sum of the correlations of the placed production materials with the production materials in the adjacent positions thereof is maximized, further comprising:
generating a vertex diagram comprising M +1 vertexes by taking the appointed point and the optimal M position as vertexes; wherein the starting point of the vertex graph is the designated point;
and planning a path of the vertex diagram by adopting a Dijkstra algorithm to obtain a path with the shortest sum of distances from the specified point to other vertexes, so that a user can place the M production materials according to the shortest path.
In this embodiment, after determining the placement of the M production materials on the N empty locations, the user can deposit the M production materials. The storage can be manual storage or automatic storage (such as robot moving storage), and when the storage is performed, a user needs to reach the determined M vacant positions in sequence to place the corresponding M production materials at one time, so that a reasonable path needs to be determined to improve the storage efficiency.
In this embodiment, dijkstra's algorithm is adopted to determine the optimal placement path. The Dijkstra algorithm belongs to one of greedy algorithms, and the search idea is to expand outward layer by taking a starting point as a center until the starting point is expanded to an end point, so that the total path of M recommended positions before access is shortest.
Assume that the vertex diagram is shown in FIG. 3, where the designated point is point D (e.g., the entrance of the warehouse is designated as the designated point), and points A, B, C, D, E, and F are 6 determined vacancies for production materials.
Specifically, the set S and the set U are set first. S is used to record the vertices (and corresponding shortest path lengths) for which the shortest path has been found, and U is used to record the vertices (and distances from the vertices to the starting point S) for which the shortest path has not been found.
(1) Initially, only a starting point D exists in S; in U are vertices other than the start point, and the path of a vertex in U is the path from the start point to the vertex.
(2) Finding out the top point with the shortest path from the U, and moving the top point from the U to the S to be used as a new starting point; then, updating the path corresponding to the vertex to the new starting point in the U
(3) Then, the vertex with the shortest path is found out from the U and added into the S \8230, and the operation is repeated until all the vertices are traversed.
The operation of the present embodiment will be described in detail with reference to fig. 3.
Step 1: vertex D is added to S.
As in fig. 3 (a), at this time, S = { D (0) }, U = { a (∞), B (∞), C (3), E (4), F (∞), G (∞) }.
Here, C (3) indicates that the distance from C to the starting point D is 3.
Step 2: vertex C is added to S.
After the operation of the previous step, the distance from the vertex C to the starting point D in the U is shortest; therefore, C is added to S, while the distance of the vertices in U is updated. Taking the vertex F as an example, the distance from F to D is infinity; but after adding C to S, the distance from F to D is 9= (F, C) + (C, D).
As in fig. 3 (B), at this time, S = { D (0), C (3) }, U = { a (∞), B (23), E (4), F (9), G (∞) }.
And 3, step 3: vertex E is added to S.
After the operation of the previous step, the distance from the vertex E to the starting point D in the U is shortest; therefore, E is added to S, while the distance of the vertices in U is updated. Or taking the vertex F as an example, the distance from F to D is 9; but after adding E to S, the distance from F to D is 6= (F, E) + (E, D).
As in fig. 3 (C), at this time, S = { D (0), C (3), E (4) }, U = { a (∞), B (23), F (6), G (12) }.
And 4, step 4: vertex F is added to S.
As in fig. 3 (D), at this time, S = { D (0), C (3), E (4), F (6) }, U = { a (22), B (13), G (12) }.
And 5, step 5: vertex G is added to S.
As in fig. 3 (E), at this time, S = { D (0), C (3), E (4), F (6), G (12) }, U = { a (22), B (13) }.
And 6, a step of: vertex B is added to S.
As in fig. 3 (F), at this time, S = { D (0), C (3), E (4), F (6), G (12), B (13) }, U = { a (22) }.
And 7, step 7: vertex a is added to S.
As in fig. 3 (G), at this time, S = { D (0), C (3), E (4), F (6), G (12), B (13), a (22) }.
Through the above steps, at this time, the shortest distance from the starting point D to each vertex is calculated as: a (22) B (13) C (3) D (0) E (4) F (6) G (12).
In the embodiment, the shortest distance from the starting point D to each vertex is obtained by adopting a Dijkstra algorithm, so that a user or a robot can store the M production materials by adopting the shortest path, and the storage efficiency is improved.
Referring to fig. 4, a production material storage device according to a second embodiment of the present invention includes:
a vacancy acquiring unit 210, configured to acquire M production materials to be currently stored and N vacancies on a shelf of a current warehouse;
an adjacent information acquiring unit 220 for acquiring information of the production materials placed at adjacent positions of each empty space;
a placement position calculation unit 230 for calculating placement positions of the M production materials in the N vacant positions based on the correlation between the production materials so that the sum of the correlations of the placed production materials with the production materials in the adjacent positions thereof is maximized.
Preferably, the correlation between two production materials is used to indicate the probability that two production materials appear in the same delivery slip at the same time, and the higher the correlation is, the higher the probability that two production materials appear in the same delivery slip at the same time is.
Preferably, the method further comprises the following steps:
the historical delivery order acquisition unit is used for acquiring a plurality of historical delivery orders; wherein each historical delivery list comprises a plurality of production materials;
and the correlation calculation unit is used for calculating the correlation among the production materials according to the distribution condition of the production materials of each historical delivery list.
Preferably, the placement position calculation unit 230 is specifically configured to:
acquiring all possible combination modes of placing the M production materials into the N vacant positions in a permutation and combination mode;
and calculating the sum of the correlations of each combination mode, and obtaining the combination mode with the maximum sum of the correlations to obtain the placement positions of the M production materials in the N vacant positions.
Preferably, the placement position calculating unit 230 is specifically configured to:
and taking the sum of the correlations as a fitness function of a particle swarm algorithm, iteratively searching for an optimal correlation combination parameter through a particle swarm, and finding out the optimal M position arrangement from the N vacancies according to the optimal correlation combination parameter so as to obtain the placement positions of the M production materials in the N vacancies.
Preferably, the placement position calculation unit 230 is specifically used for
Initializing a particle swarm; the method comprises the steps of initializing and setting the number of populations, randomly setting M position arrangements, maximum evolution algebra and upper and lower limits of inertia weight; randomly initializing the position and speed of the search point, and setting the Pbest of each particle i (0) Calculating individual extreme value of the particle for the current position, recording the individual maximum value and the particle serial number of the whole population, and setting Nbest i (0) Is the current position of the largest particle;
calculating the fitness of each particle, comparing the fitness with the current individual extremum of the particle, and updating the optimal position Pbest of each particle i (t), finding out the maximum value of the individual extreme values of all the particles, comparing the maximum value with the current maximum value, if the maximum value exceeds the current maximum value, recording the serial number of the maximum particle, and updating the current position of the maximum particle to Nbest i (t)；
Updating the velocity and position of each particle;
judging whether the current iteration number meets the maximum value T max Or whether the error is smaller than the minimum threshold value or not, if so, stopping iteration and outputting the optimal correlation combination parameter, otherwise, returning to the step S2;
and finding out the optimal M position arrangements from the N empty positions according to the optimal correlation combination parameters.
Preferably, the method further comprises the following steps:
a vertex map generating unit for generating a vertex map including M +1 vertices with the designated point and the optimal M positions as vertices; wherein the starting point of the vertex graph is the designated point;
and the path planning unit is used for carrying out path planning on the vertex diagram by adopting a Dijkstra algorithm to obtain a path with the shortest sum of the distances from the specified point to other vertexes, so that the user can place the M production materials according to the shortest path.
The third embodiment of the present invention further provides a production material storage apparatus, which includes a memory and a processor, wherein the memory stores a computer program, and the computer program can be executed by the processor to implement the production material storage method.
The fourth embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored, where the computer program can be executed by a processor of an apparatus where the computer-readable storage medium is located, so as to implement the production material storage method as described above.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, 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 that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part thereof which substantially contributes to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, an electronic device, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. A production material storage method, comprising:
acquiring M production materials to be stored currently and N vacant positions on a shelf of a current warehouse;
obtaining information of production materials placed at adjacent positions of each vacancy;
calculating placement positions of the M production materials in the N vacant positions according to the correlation between the production materials so that the sum of the correlation between the placed production materials and the production materials at the adjacent positions thereof is maximum; the relevance between the two production materials is used for indicating the probability that the two production materials simultaneously appear in the same delivery receipt, and the higher the relevance is, the higher the probability that the two production materials simultaneously appear in the same delivery receipt is; the method specifically comprises the following steps:
taking the sum of the correlations as a fitness function of a particle swarm algorithm, iteratively searching for an optimal correlation combination parameter through a particle swarm, and finding out the optimal M position arrangement from the N vacancies according to the optimal correlation combination parameter so as to obtain the placement positions of the M production materials in the N vacancies; taking the sum of the correlations as a fitness function of a particle swarm algorithm, iteratively searching for an optimal correlation combination parameter through a particle swarm, and finding out an optimal M position arrangement from N vacancies according to the optimal correlation combination parameter to obtain the placement positions of the M production materials in the N vacancies, specifically comprising the following steps:
s1, initializing a particle swarm; the method comprises the steps of initializing and setting the number of populations, randomly setting M position arrangements, maximum evolution algebra and upper and lower limits of inertia weight; randomly initializing the position and speed of the search point, and setting the Pbest of each particle i (0) Calculating individual extreme value of the particle for the current position, recording the individual maximum value and the particle serial number of the whole population, and setting Nbest i (0) Is the current position of the largest particle;
s2, calculating the fitness of each particle, comparing the fitness with the current individual extreme value of the particle, and updating the optimal position Pbest of each particle i (t), finding out the maximum value of the individual extreme values of all the particles, comparing the maximum value with the current maximum value, if the maximum value exceeds the current maximum value, recording the serial number of the maximum particle, and updating the current position of the maximum particle to Nbest i (t)；
S3, updating the speed and the position of each particle;
s4, judging whether the current iteration number meets the maximum value T or not max Or whether the error is smaller than the minimum threshold value or not, if so, stopping iteration and outputting the optimal correlation combination parameter, otherwise, returning to the step S2;
s5: and finding out the optimal M position arrangements from the N empty positions according to the optimal correlation combination parameters.
2. The production material stocking method according to claim 1, further comprising, before calculating placement positions of the M production materials in the N vacant positions based on the correlation between the production materials so that a sum of the correlations of the placed production material with the production materials in its adjacent positions is maximized:
acquiring a plurality of historical delivery lists; wherein each historical delivery list comprises a plurality of production materials;
and calculating the correlation among the production materials according to the distribution condition of the production materials of each historical delivery list.
3. A production material storage device, comprising:
the vacancy acquisition unit is used for acquiring M production materials to be stored currently and N vacancies on a shelf of a current warehouse;
an adjacent information acquisition unit for acquiring information of the production materials placed in adjacent positions of each vacancy;
a placement position calculation unit for calculating placement positions of the M production materials in the N vacant positions based on correlations between the production materials so that a sum of correlations of the placed production materials with the production materials in the adjacent positions thereof is maximized; the correlation between the two production materials is used for representing the probability that the two production materials simultaneously appear in the same delivery list, and the higher the correlation is, the higher the probability that the two production materials simultaneously appear in the same delivery list is; wherein the placement position calculation unit is specifically configured to:
taking the sum of the correlations as a fitness function of a particle swarm algorithm, iteratively searching for an optimal correlation combination parameter through a particle swarm, and finding out the optimal M position arrangement from the N vacancies according to the optimal correlation combination parameter so as to obtain the placement positions of the M production materials in the N vacancies; taking the sum of the correlations as a fitness function of a particle swarm algorithm, iteratively searching for an optimal correlation combination parameter through a particle swarm, and finding out an optimal M position arrangement from N vacancies according to the optimal correlation combination parameter so as to obtain the placement positions of the M production materials in the N vacancies, wherein the method specifically comprises the following steps:
s1, initializing a particle swarm; the method comprises the steps of initializing and setting the number of populations, randomly setting M position arrangements, maximum evolution algebra and upper and lower limits of inertia weight; randomly initializing the position and speed of the search point, and setting the Pbest of each particle i (0) Calculating individual extreme value of the particle for the current position, recording the individual maximum value and the particle serial number of the whole population, and setting Nbest i (0) Is the current position of the largest particle;
s2, calculating the fitness of each particle, comparing the fitness with the current individual extreme value of the particle, and updating the optimal position Pbest of each particle i (t), finding out the maximum value of the individual extreme values of all the particles, comparing the maximum value with the current maximum value, if the maximum value exceeds the current maximum value, recording the serial number of the maximum particle, and updating the current position of the maximum particle to Nbest i (t)；
S3, updating the speed and the position of each particle;
s4, judging whether the current iteration number meets the maximum value T or not max Or whether the error is smaller than the minimum threshold value or not, if so, stopping iteration and outputting the optimal correlation combination parameter, otherwise, returning to the step S2;
s5: and finding out the optimal M position arrangements from the N vacant positions according to the optimal correlation combination parameters.
4. A production material storage apparatus comprising a memory and a processor, the memory storing a computer program executable by the processor to implement the production material storage method according to any one of claims 1 to 2.
5. A computer-readable storage medium, in which a computer program is stored, the computer program being executable by a processor of an apparatus in which the computer-readable storage medium is stored to implement the production material deposit method according to any one of claims 1 to 2.
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