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Flexible job shop multi-target scheduling method and system based on improved genetic algorithm

An improved genetic algorithm and flexible operation technology, applied in the field of flexible job shop multi-objective scheduling, can solve the problems of inaccurate solution results of flexible job shop scheduling optimization, not considering processing auxiliary time and resource constraints, and achieve true and accurate solution results. , solve the effect of accurate results

Active Publication Date: 2021-12-21
HEFEI UNIV OF TECH
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  • Description
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  • Application Information

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Problems solved by technology

[0006] Aiming at the deficiencies of the prior art, the present invention provides a flexible job shop multi-objective scheduling method and system based on an improved genetic algorithm, which solves the problem of the optimization solution of the flexible job shop scheduling due to the lack of consideration of processing auxiliary time and resource constraints in the prior art The problem with inaccurate results

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  • Flexible job shop multi-target scheduling method and system based on improved genetic algorithm
  • Flexible job shop multi-target scheduling method and system based on improved genetic algorithm
  • Flexible job shop multi-target scheduling method and system based on improved genetic algorithm

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Embodiment 1

[0143] In the first aspect, the present invention firstly proposes a multi-objective scheduling method for a flexible job shop based on an improved genetic algorithm, the method comprising:

[0144] S1. Set the parameter set of the genetic algorithm; the parameter set includes: preset iterative algebra I, population size P, offspring mutation rate Pm, offspring crossover rate Pc, objective function weight α; total number of workpieces n; total number of processing equipment m , processing equipment number k, processing equipment Total number of transport machines a, transport machine number b, transport machine The total number of processes J for workpiece i i ;Process O i,j Available set of processing equipment Process O i,j Available set of transport machines

[0145] S2. Set the process part, processing equipment part and transportation machine part of the parameter set as the first substring, the second substring and the third substring of the chromosome respecti...

Embodiment 2

[0218] In the second aspect, the present invention also provides a flexible job shop multi-objective scheduling system based on an improved genetic algorithm, the system comprising:

[0219] A processing unit, the processing unit is used to perform the following steps:

[0220] S1. Set the parameter set of the genetic algorithm; the parameter set includes: preset iterative algebra I, population size P, offspring mutation rate Pm, offspring crossover rate Pc, objective function weight α; total number of workpieces n; total number of processing equipment m , processing equipment number k, processing equipment Total number of transport machines a, transport machine number b, transport machine The total number of processes J for workpiece i i ;Process O i,j Available set of processing equipment Process O i,j Available set of transport machines

[0221] S2. Set the process part, processing equipment part and transportation machine part of the parameter set as the first s...

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Abstract

The invention provides a flexible job shop multi-target scheduling method and system based on an improved genetic algorithm, and relates to the technical field of flexible job shop scheduling. To solve the scheduling optimization problem of the flexible job shop, a multi-target scheduling optimization model considering process preparation time and transportation time with resource constraints is established by taking minimization of maximum completion time and reduction of line edge inventory time as targets, and when a scheduling optimization result is solved, the model is solved by adopting an improved genetic algorithm. A three-layer coding mode is adopted, so that chromosomes can carry more information, crossover and mutation operators are designed, it is ensured that newly generated progenies are still feasible solutions, and finally the optimal solution of a scheduling optimization problem is obtained. The problem provided by the invention and the method used for solving the problem are more in line with enterprise production practice, the solving result is more accurate, and the invention has certain reference value for enterprise production.

Description

technical field [0001] The invention relates to the technical field of flexible job shop scheduling, in particular to a flexible job shop multi-objective scheduling method and system based on an improved genetic algorithm. Background technique [0002] Flexible job shop scheduling is the key for enterprises to achieve high efficiency, high quality, high flexibility, and low cost in production. However, when workpieces are processed in flexible job shops, the production and processing processes are cumbersome and complicated (for example, the flexible job shop of tires includes molding , vulcanization, manual inspection, testing machine inspection and other production processes). How to scientifically and reasonably arrange the processing sequence and processing equipment of different types of workpieces, strengthen the coordinated scheduling between equipment, improve the production efficiency of workpieces, and reduce the inventory on the production line are the focus of en...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/04G06N3/12
CPCG06Q10/06312G06Q50/04G06N3/126Y02P90/30
Inventor 胡小建黄亚领袁丁杨智
Owner HEFEI UNIV OF TECH
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