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Genetic Algorithm in Solving the Job-Shop Scheduling

Yan Chun Liang

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Abstract

Based on the mathematical model of job shop scheduling system,this paper discusses the genetic algorithm(GA) of solving Job-Shop scheduling problem,especially the method of generating feasible scheduling and GA improvement.Take the typical Job-Shop scheduling problem,FT06,as an example to verify the performance of GA and GA improvement.The test result shows that GA can not find the best result of job shop scheduling problem(FT06),but this GA improvement can usually find the best result of this scheduling problem.It also shows that the capacity of GA in resolving job shop scheduling problems is deficient,and tells that this GA improvement is feasible and much better than GA in resolving job shop scheduling problems.So the future direction of appling GA method to resolve job shop scheduling problems is GA improvement.

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What this paper is about

Based on the mathematical model of job shop scheduling system,this paper discusses the genetic algorithm(GA) of solving Job-Shop scheduling problem,especially the method of generating feasible scheduling and GA improvement.Take the typical Job-Shop scheduling problem,FT06,as an example to verify the performance of GA and GA improvement.The test result shows that GA can not find the best result of job shop scheduling problem(FT06),but this GA improvement can usually find the best result of this scheduling problem.It also shows that the capacity of GA in resolving job shop scheduling problems is deficient,and tells that this GA improvement is feasible and much better than GA in resolving job shop scheduling problems.So the future direction of appling GA method to resolve job shop scheduling problems is GA improvement.

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Available abstract

Based on the mathematical model of job shop scheduling system,this paper discusses the genetic algorithm(GA) of solving Job-Shop scheduling problem,especially the method of generating feasible scheduling and GA improvement.Take the typical Job-Shop scheduling problem,FT06,as an example to verify the performance of GA and GA improvement.The test result shows that GA can not find the best result of job shop scheduling problem(FT06),but this GA improvement can usually find the best result of this scheduling problem.It also shows that the capacity of GA in resolving job shop scheduling problems is deficient,and tells that this GA improvement is feasible and much better than GA in resolving job shop scheduling problems.So the future direction of appling GA method to resolve job shop scheduling problems is GA improvement.

Key concepts: Flow shop scheduling, Job shop scheduling, Rate-monotonic scheduling, Fair-share scheduling, Dynamic priority scheduling, Computer science, Mathematical optimization, Two-level scheduling

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