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Genetic Algorithm Based Approach for Intelligent Scheduling Optimization of Multi- resources

Zhu Jianyin

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Abstract

Abstract:This paper presents a scheduling approach, based on Genetic Algorithms (GA), developed to address the scheduling problem in manufacturing systems constrained by machines, workers and robots. The objective of scheduling problems is to minimize makespan. The genetic algorithms combining with dispatching rules is used. After using crossover and mutation operations, a best or second best scheduling plan can be found. Computer simulation is conducted, and the simulation results are given.

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What this paper is about

Abstract:This paper presents a scheduling approach, based on Genetic Algorithms (GA), developed to address the scheduling problem in manufacturing systems constrained by machines, workers and robots. The objective of scheduling problems is to minimize makespan. The genetic algorithms combining with dispatching rules is used. After using crossover and mutation operations, a best or second best scheduling plan can be found. Computer simulation is conducted, and the simulation results are given.

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Available abstract

Abstract:This paper presents a scheduling approach, based on Genetic Algorithms (GA), developed to address the scheduling problem in manufacturing systems constrained by machines, workers and robots. The objective of scheduling problems is to minimize makespan. The genetic algorithms combining with dispatching rules is used. After using crossover and mutation operations, a best or second best scheduling plan can be found. Computer simulation is conducted, and the simulation results are given.

Key concepts: Job shop scheduling, Crossover, Genetic algorithm scheduling, Computer science, Scheduling (production processes), Fair-share scheduling, Two-level scheduling, Dynamic priority scheduling

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