CN117371621A - Library position distribution method, system and medium based on improved drosophila optimization algorithm - Google Patents
Library position distribution method, system and medium based on improved drosophila optimization algorithm Download PDFInfo
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- 241000255581 Drosophila <fruit fly, genus> Species 0.000 title claims abstract description 72
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- 238000005457 optimization Methods 0.000 title claims abstract description 38
- 238000004422 calculation algorithm Methods 0.000 title claims abstract description 37
- 238000009826 distribution Methods 0.000 title claims description 13
- 238000003860 storage Methods 0.000 claims abstract description 102
- 108700023136 Drosophila Set Proteins 0.000 claims description 12
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- 230000009286 beneficial effect Effects 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 3
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
Abstract
The invention discloses a bin allocation method, a system and a medium based on an improved drosophila optimization algorithm, which relate to the technical field of warehouse scheduling, and the method comprises the following steps: acquiring basic information of a target cargo; determining goods to be put in storage in a target period and the remaining conditions of the stacker library positions in the target goods; and determining the optimal placement position of the goods to be put in the target period based on the goods to be put in the warehouse, the residual condition and an improved drosophila optimization algorithm, and completing the allocation of the warehouse positions of the crenelers of the goods to be put in the warehouse. According to the invention, the improved drosophila optimization algorithm can generate a library position allocation strategy according to the order situation in a certain time window issued by the upstream system, and then the library position allocation strategy is issued to the downstream system to control the stacker to execute the picking and placing tasks.
Description
Technical Field
The invention relates to the technical field of warehouse scheduling, in particular to a warehouse position distribution method, a system and a medium based on an improved drosophila optimization algorithm.
Background
Unmanned warehouse logistics have been developed in China for many years, however, with the rapid development of industry and continuous change of business modes, more and more enterprises have put requirements on warehouse position allocation strategies of automatic stereoscopic warehouse of the stacker, so a set of optimization algorithm is needed to further improve the storage efficiency of the stacker warehouse, and the goods can be allocated on the most reasonable warehouse positions. However, the mainstream solution idea still distributes the goods space through simple rules and region division, so the degree of efficiency optimization is not ideal enough, and therefore, a group intelligent optimization algorithm needs to be introduced to generate a stock allocation strategy according to the order situation.
Disclosure of Invention
The invention aims to solve the technical problems of the prior art, particularly aims to solve the problem of rationality of bin allocation in a stacker warehouse, and particularly provides a bin allocation method, a system and a medium based on an improved drosophila optimization algorithm, wherein the method comprises the following steps:
1) In a first aspect, the invention provides a stacker base position allocation method based on an improved drosophila optimization algorithm, which comprises the following specific technical scheme:
acquiring basic information of a target cargo;
determining goods to be put in storage in a target period and the residual condition of each stacker library position in the target goods;
and determining the optimal placement position of the goods to be put in the target period based on the basic information, the goods to be put in storage, all the rest conditions and an improved drosophila optimization algorithm, and completing the allocation of the warehouse positions of the pusher of the goods to be put in storage.
The stacker library position allocation method based on the improved drosophila optimization algorithm has the following beneficial effects:
when the improved drosophila optimization algorithm is used for generating a bin allocation scheme, the improved drosophila optimization algorithm generates a bin allocation strategy according to the order situation in a certain time window issued by an upstream system, and then issues the bin allocation strategy to a downstream system to control a stacker to execute a picking and placing task.
On the basis of the scheme, the invention can be improved as follows.
Further, the base information includes: the mass of the target cargo and the turnover rate of the target cargo.
Further, the process of determining the optimal placement position of the goods to be put in storage in the target period is as follows:
generating an initial drosophila population based on the basic information of the goods to be put in storage and the residual conditions;
determining a search step length corresponding to the current iteration, and generating a drosophila set according to the search step length and an olfactory search mechanism, wherein each drosophila in the drosophila set represents a unpiler library allocation scheme after being encoded according to an encoding rule;
calculating the fitness of each drosophila in the drosophila set based on a fitness function;
and cycling the drosophila with the minimum adaptability as the position of the drosophila population of the next iteration until the iteration times are met, and taking a crenel pusher library position allocation scheme corresponding to the drosophila with the minimum adaptability in the current iteration period as the optimal placement position of the goods to be put in storage.
Further, the initial drosophila population process is:
determining a transport attribute value corresponding to each cargo to be put in storage based on a transport attribute calculation formula, and coding each cargo to be put in storage;
coding all the crenel stock positions, and determining that each residual condition is the physical distance from the center point of the corresponding crenel stock position to the entrance and the exit of the crenel stock;
according to the transport attribute value, descending order of goods to be put into storage is carried out, a first queue is generated, ascending order of the corresponding pusher storage positions is carried out according to the physical distance, a second queue is generated, codes at corresponding positions in the first queue and the second queue are sequentially associated according to the sequence, and the associated codes are used as initial drosophila groups.
Further, the attribute calculation formula specifically includes:
；
wherein,representing the transport attribute of the ith goods to be put in storage; />The weight of the ith goods to be put in storage is the weight of the ith goods to be put in storage; />And the turnover rate of the ith goods to be put in storage is represented.
Further, the search step length corresponding to the current iteration is determined specifically as follows:
the determination of the search step S is performed by a first formula:
；
wherein M represents the total number of goods to be put in storage, N represents the upper limit value of the maximum number of iterations, N is the current number of iterations, round #) Representation pair->Rounding is performed.
Further, the olfactory search mechanism is:
and randomly selecting a plurality of codes with the number equal to the searching step length from the code string, and forming a matching set by the bank bits of the crenel corresponding to the rest condition, wherein the matching set is selected with the number equal to the searching step length and is filled in the code string.
Further, the fitness function is specifically:
；
wherein,representing the coding of the library bit corresponding to the a-th bit in the drosophila coding string,/for>And c represents the relative constant coefficient of the transportation attribute of the goods to be put in storage.
2) In a second aspect, the invention also provides a stacker garage position distribution system based on an improved drosophila optimization algorithm, and the stacker garage position distribution system has the following specific technical scheme:
the acquisition module is used for: acquiring basic information of a target cargo;
the determining module is used for: determining goods to be put in storage in a target period and the residual condition of each stacker library position in the target goods;
the distribution module is used for: and determining the optimal placement position of the goods to be put in the target period based on the basic information, the goods to be put in storage, all the rest conditions and an improved drosophila optimization algorithm, and completing the allocation of the warehouse positions of the pusher of the goods to be put in storage.
3) In a third aspect, the present invention also provides a computer readable storage medium having stored therein at least one computer program loaded and executed by a processor to cause a computer to implement a method as in any of the above.
It should be noted that, the technical solutions of the second aspect to the third aspect and the corresponding possible implementation manners of the present invention may refer to the technical effects of the first aspect and the corresponding possible implementation manners of the first aspect, which are not described herein.
Drawings
Other features, objects and advantages of the present invention 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 stacker pool allocation method based on an improved Drosophila optimization algorithm according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a scheduling flow of a stacker pool allocation method based on an improved drosophila optimization algorithm according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the embodiments of the present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, the stacker base position allocation method based on the improved drosophila optimization algorithm in the embodiment of the invention comprises the following steps:
s1, acquiring basic information of target goods;
s2, determining goods to be put in storage in a target period and the residual condition of each stacker bin in the target goods;
and S3, determining the optimal placement position of the goods to be put in the target period based on the basic information, the goods to be put in storage, all the residual conditions and an improved fruit fly optimization algorithm, and completing the allocation of the warehouse positions of the pusher of the goods to be put in storage.
The stacker library position allocation method based on the improved drosophila optimization algorithm has the following beneficial effects:
when the improved drosophila optimization algorithm is used for generating a bin allocation scheme, the improved drosophila optimization algorithm generates a bin allocation strategy according to the order situation in a certain time window issued by an upstream system, and then issues the bin allocation strategy to a downstream system to control a stacker to execute a picking and placing task.
As shown in fig. 2, the process of acquiring the basic information of the target cargo specifically includes:
and acquiring basic information of the goods to be put in storage according to the order condition issued by the upstream system, wherein the basic information comprises the volume, the quality and the turnover rate of the goods.
Upstream systems refer to: a system stores order information, i.e., basic information of goods to be put in storage.
The order case refers to: orders generated by systems such as production/sales systems to indicate which specific goods are to be entered into the stacker for storage.
The remainder of the stacker pool bits generally refers to whether each stacker pool bit is empty.
The process for determining the optimal placement position of the goods to be put in storage comprises the following steps:
generating an initial drosophila population through the basic information of the goods to be put in storage and the residual storage position information;
the method for generating the initial drosophila population specifically comprises the following steps:
firstly, calculating the transportation attribute value of each cargo according to a transportation attribute calculation formula;
the attribute calculation formula is:
wherein,representing the transport attribute of the ith goods to be put in storage, wherein the larger the value is, the more the goods i should be stored at a position close to the warehouse-in and warehouse-out port of the stacker, and the warehouse-in and warehouse-out port represents a common port for warehouse-out and warehouse-in; />The weight of the ith goods to be put in storage is the weight of the ith goods to be put in storage; />And the turnover rate of the ith goods to be put in storage is represented.
Coding all the library bits, screening out the residual library bit codes, and calculating the physical distance from the center of each residual library bit to the entrance;
the library center refers to: and calculating physical coordinates relative to the stacker in-out warehouse opening according to the warehouse position width and height and the warehouse position.
The physical distance from the center of the library to the entrance is determined in the following way: according to Pythagorean theorem, calculating the physical distance from the entrance of the stacker to the center of the corresponding warehouse.
The library bits are encoded in sequential increments, such as: the storage positions are arranged in the sequence from the nearest end of the stacker entrance to the farthest end of the stacker entrance from bottom to top, and the storage positions are progressively ordered from 0.
Screening out the residual library bit codes, namely: and coding all the occupied and unoccupied unpiler bank positions, wherein the unoccupied unpiler bank position codes are the rest bank position codes.
And (3) arranging the cargo transportation attribute values in a descending order, arranging the distances of the remaining storage positions in an ascending order, and corresponding the storage position codes after the ascending order and the cargo codes after the descending order according to the cargo transportation attribute values, wherein the storage position codes are used as initial drosophila groups. The drosophila codes are stored in an array form, each storage value in the array represents the corresponding library bit code, and the array subscript represents the serial number of the corresponding goods to be put in storage.
The method for confirming the searching step length in iteration comprises the following steps:
wherein M represents the total number of goods to be put in storage, N represents the upper limit value of the maximum number of iterations, N is the current number of iterations, round #) Representation pair->Rounding is performed. The step size calculation formula gradually reduces the searching step size of the drosophila according to the increase of the iteration times.
The olfactory search mechanism is:
several bits with the same number as the search step length are randomly selected in the code string, the rest library bits with the non-selection form a set, and the values with the same number of the search step length are selected in the set to be filled in the original code string.
The code string is assumed to have 5 cargoes to be put in storage, 10 available storage bits, and takes an array C5= [1,9,3,7,6] as an example, the length of the array represents the total number of cargoes to be put in storage, and the ci represents the storage bit code allocated to the ith cargoes to be put in storage.
For example: in the code string C [5] = [1,9,3,7,6], 2 bits equal to the search step 2 are randomly selected, such as selecting [3,7], and then the code string is encoded with the rest library bits to form a set {0,2,3,4,5,7,8}, 2 bits equal to the search step 2 are randomly selected in the set, such as selecting [7,0], and then the original code string is sequentially filled to form a new code string C' [5] = [1,9,7,0,6].
And calculating the fitness of each drosophila according to the fitness function.
The specific method for calculating the fitness function comprises the following steps:
；
wherein,representing the coding of the library bit corresponding to the a-th bit in the drosophila coding string,/for>And c represents the correlation constant coefficient of the transportation attribute of the goods to be put in storage, and the transportation attributes of different goods to be put in storage all adopt the same correlation constant coefficient.
Arranging the fitness in a descending order, and selecting the drosophila with the smallest fitness function value as the position of the drosophila population of the next iteration;
repeating the above cycle until the iteration times meet the requirement.
And controlling the stacker to take and put goods according to the optimal scheduling scheme, wherein the action is controlled by the lower system in hardware.
The lower level system is generally referred to as: the system for controlling the stacker to perform tasks is typically a PLC program.
Further, the base information includes: the volume of the target cargo, the mass of the target cargo, and the turnover rate of the target cargo.
Further, the process of determining the optimal placement position of the goods to be put in storage in the target period is as follows:
generating an initial drosophila population based on the basic information of the goods to be put in storage and the residual conditions;
determining a search step length corresponding to the current iteration, and generating a drosophila set according to the search step length and an olfactory search mechanism, wherein each drosophila in the drosophila set represents a unpiler library allocation scheme after being encoded according to an encoding rule;
calculating the fitness of each drosophila in the drosophila set based on a fitness function;
and (3) taking the drosophila with the minimum adaptability as the position of the drosophila population of the next iteration to circulate until the iteration times are met.
Further, the initial drosophila population process is:
determining a transport attribute value corresponding to each cargo to be put in storage based on a transport attribute calculation formula, and coding each cargo to be put in storage;
coding all the crenel stock positions, and determining that each residual condition is the physical distance from the center point of the corresponding crenel stock position to the entrance and the exit of the crenel stock;
according to the transport attribute value, descending order of goods to be put into storage is carried out, a first queue is generated, ascending order of the corresponding pusher storage positions is carried out according to the physical distance, a second queue is generated, codes at corresponding positions in the first queue and the second queue are sequentially associated according to the sequence, and the associated codes are used as initial drosophila groups.
Further, the attribute calculation formula specifically includes:
；
wherein,representing the transport attribute of the ith goods to be put in storage; />The weight of the ith goods to be put in storage is the weight of the ith goods to be put in storage; />And the turnover rate of the ith goods to be put in storage is represented.
Further, the search step length corresponding to the current iteration is determined specifically as follows:
the determination of the search step S is performed by a first formula:
；
wherein M represents the total number of goods to be put in storage, N represents the upper limit value of the maximum number of iterations, N is the current number of iterations, round #) Representation pair->Rounding is performed.
Further, the olfactory search mechanism is:
and randomly selecting a plurality of codes with the number equal to the searching step length from the code string, and forming a matching set by the bank bits of the crenel corresponding to the rest condition, wherein the matching set is selected with the number equal to the searching step length and is filled in the code string.
Further, the fitness function is specifically:
；
wherein,representing the coding of the library bit corresponding to the a-th bit in the drosophila coding string,/for>And c represents the relative constant coefficient of the transportation attribute of the goods to be put in storage.
The invention also provides a stacker library position distribution system based on the improved drosophila optimization algorithm, which comprises the following specific technical scheme:
the acquisition module is used for: acquiring basic information of a target cargo;
the determining module is used for: determining goods to be put in storage in a target period and the residual condition of each stacker library position in the target goods;
the distribution module is used for: and determining the optimal placement position of the goods to be put in the target period based on the basic information, the goods to be put in storage, all the rest conditions and an improved drosophila optimization algorithm, and completing the allocation of the warehouse positions of the pusher of the goods to be put in storage.
In the above embodiments, although steps S1, S2, etc. are numbered, only specific embodiments of the present invention are given, and those skilled in the art may adjust the execution sequence of S1, S2, etc. according to the actual situation, which is also within the scope of the present invention, and it is understood that some embodiments may include some or all of the above embodiments.
It should be noted that, the beneficial effects of the stacker base position distribution system based on the improved fruit fly optimization algorithm provided in the above embodiment are the same as the beneficial effects of the stacker base position distribution method based on the improved fruit fly optimization algorithm described above, and are not described here again. In addition, when the system provided in the above embodiment implements the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the system is divided into different functional modules according to practical situations, so as to implement all or part of the functions described above. In addition, the system and method embodiments provided in the foregoing embodiments belong to the same concept, and specific implementation processes thereof are detailed in the method embodiments and are not described herein again.
A computer-readable storage medium according to an embodiment of the present invention stores at least one computer program therein, and the at least one computer program is loaded and executed by a processor to cause a computer to implement any one of the methods described above.
Alternatively, the computer readable storage medium may be a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a compact disc Read-Only Memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.
In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium and executes the computer instructions to cause the computer device to perform any of the methods described above.
It should be noted that the terms "first," "second," and the like in the description and in the claims of the present application are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. The order of use of similar objects may be interchanged where appropriate so that embodiments of the present application described herein may be implemented in other sequences than those illustrated or described.
Those skilled in the art will appreciate that the present invention may be embodied as a system, method or computer program product, and that the disclosure may therefore be embodied in the form of: either entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or entirely software, or a combination of hardware and software, referred to herein generally as a "circuit," module "or" system. Furthermore, in some embodiments, the invention may also be embodied in the form of a computer program product in one or more computer-readable media, which contain computer-readable program code.
Any combination of one or more computer readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (9)
1. The stacker base position distribution method based on the improved drosophila optimization algorithm is characterized by comprising the following steps of:
acquiring basic information of a target cargo;
determining goods to be put in storage in a target period and the residual condition of each stacker library position in the target goods;
determining the optimal placement position of the goods to be put in storage in the target period based on the basic information, the goods to be put in storage, all the rest conditions and an improved drosophila optimization algorithm, and completing the allocation of the storage positions of the pusher of the goods to be put in storage;
the process of determining the optimal placement position of the goods to be put in storage in the target period is as follows:
generating an initial drosophila population based on the basic information of the goods to be put in storage and the residual conditions;
determining a search step length corresponding to the current iteration, and generating a drosophila set according to the search step length and an olfactory search mechanism, wherein each drosophila in the drosophila set represents a unpiler library allocation scheme after being encoded according to an encoding rule;
calculating the fitness of each drosophila in the drosophila set based on a fitness function;
and cycling the drosophila with the minimum adaptability as the position of the drosophila population of the next iteration until the iteration times are met, and taking a crenel pusher library position allocation scheme corresponding to the drosophila with the minimum adaptability in the current iteration period as the optimal placement position of the goods to be put in storage.
2. The stacker pool level assignment method based on the improved drosophila optimization algorithm of claim 1, wherein the base information comprises: the mass of the target cargo and the turnover rate of the target cargo.
3. The stacker pool level assignment method based on the improved drosophila optimization algorithm of claim 1, wherein the initial drosophila population process is:
determining a transport attribute value corresponding to each cargo to be put in storage based on a transport attribute calculation formula, and coding each cargo to be put in storage;
coding all the crenel stock positions, and determining that each residual condition is the physical distance from the center point of the corresponding crenel stock position to the entrance and the exit of the crenel stock;
according to the transport attribute value, descending order of goods to be put into storage is carried out, a first queue is generated, the storage positions of the crenelers with the remaining conditions being the physical distance are ascending order arranged, a second queue is generated, codes at corresponding positions in the first queue and the second queue are sequentially associated according to the order, and the associated codes are used as initial drosophila groups.
4. The stacker pool level assignment method based on the improved drosophila optimization algorithm of claim 3, wherein the attribute calculation formula specifically comprises:
；
wherein,representing the transport attribute of the ith goods to be put in storage; />The weight of the ith goods to be put in storage is the weight of the ith goods to be put in storage; />And the turnover rate of the ith goods to be put in storage is represented.
5. The stacker pool-level assignment method based on the improved drosophila optimization algorithm of claim 1, wherein determining the search step corresponding to the current iteration is specifically:
searching step length through a first formulaThe first formula is:
；
wherein M represents the total number of goods to be put in storage, N represents the maximum iteration number, N is the current iteration number, and round #) Representation pair->Rounding is performed.
6. The stacker pool level assignment method based on the improved drosophila optimization algorithm of claim 4, wherein the olfactory search mechanism is:
randomly selecting codes with the number equal to the searching step length from the code strings, and forming a matching set with the base bits of the pusher with the number equal to the searching step length, wherein the number equal to the searching step length is selected from the matching set, and the values with the number equal to the searching step length are filled in the code strings.
7. The stacker pool level assignment method based on the improved drosophila optimization algorithm of claim 6, wherein the fitness function is specifically:
；
wherein,representing the coding of the library bit corresponding to the a-th bit in the drosophila coding string,/for>And c represents the relative constant coefficient of the transportation attribute of the goods to be put in storage.
8. Stacker base position distribution system based on improve fruit fly optimization algorithm, characterized by comprising:
the acquisition module is used for: acquiring basic information of a target cargo;
the determining module is used for: determining goods to be put in storage in a target period and the residual condition of each stacker library position in the target goods;
the distribution module is used for: determining the optimal placement position of the goods to be put in storage in the target period based on the basic information, the goods to be put in storage, all the rest conditions and an improved drosophila optimization algorithm, and completing the allocation of the storage positions of the pusher of the goods to be put in storage;
the process of determining the optimal placement position of the goods to be put in storage in the target period is as follows:
generating an initial drosophila population based on the basic information of the goods to be put in storage and the residual conditions;
determining a search step length corresponding to the current iteration, and generating a drosophila set according to the search step length and an olfactory search mechanism, wherein each drosophila in the drosophila set represents a unpiler library allocation scheme after being encoded according to an encoding rule;
calculating the fitness of each drosophila in the drosophila set based on a fitness function;
and cycling the drosophila with the minimum adaptability as the position of the drosophila population of the next iteration until the iteration times are met, and taking a crenel pusher library position allocation scheme corresponding to the drosophila with the minimum adaptability in the current iteration period as the optimal placement position of the goods to be put in storage.
9. A computer readable storage medium having stored therein at least one computer program that is loaded and executed by a processor to cause a computer to implement the method of any one of claims 1 to 7.
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| CN117592760B (en) * | 2024-01-18 | 2024-04-09 | 湖北浩蓝智造科技有限公司 | Method, system, equipment and medium for distributing warehouse-in and warehouse-out tasks of stacker |
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