Hybrid particle swarm optimization for flexible job-shop scheduling problem and its implementation

In this paper, a hybrid integer programming model is proposed for flexible job-shop scheduling problem(FJSP). Using crossover operator and mutation operator, the hybrid particle swarm optimization(HPSO) algorithm with basic particle swarm optimization(BPSO) algorithm and genetic algorithm(GA) is emp...

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Bibliographic Details
Published inThe 2010 IEEE International Conference on Information and Automation pp. 1155 - 1159
Main Authors Xu, Xiao-hong, Zeng, Ling-li, Fu, Yue-wen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2010
Subjects
Automation
Educational institutions
Flexible Job-shop
Genetic mutations
Hybrid particle swarm optimization
Iterative algorithms
Linear programming
Mathematical model
Mathematical programming
NP-hard problem
Particle swarm optimization
Scheduling
Simulation Software
Software algorithms
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Summary:In this paper, a hybrid integer programming model is proposed for flexible job-shop scheduling problem(FJSP). Using crossover operator and mutation operator, the hybrid particle swarm optimization(HPSO) algorithm with basic particle swarm optimization(BPSO) algorithm and genetic algorithm(GA) is employed to solve this problem. Compared with BPSO algorithm, HPSO algorithm has a potential to reach a better optimum. The simulation software for FJSP using HPSO algorithm is designed and implemented based on Object-oriented Programming Language, and the results of simulation indicate that, HPSO algorithm outperforms BPSO algorithm on searching speed for global optimum and avoiding prematurity in solving FJSP.
ISBN:1424457017
9781424457014
DOI:10.1109/ICINFA.2010.5512310