Title :
Hybrid particle swarm optimization for flexible job-shop scheduling problem and its implementation
Author :
Xu Xiao-hong ; Zeng Ling-Li ; Fu Yue-Wen
Author_Institution :
Coll. of Mechatron. & Autom., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
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.
Keywords :
genetic algorithms; integer programming; job shop scheduling; particle swarm optimisation; GA; basic particle swarm optimization algorithm; flexible job shop scheduling problem; genetic algorithm; hybrid integer programming model; hybrid particle swarm optimization algorithm; object oriented programming language; Automation; Educational institutions; Genetic mutations; Iterative algorithms; Linear programming; Mathematical model; Mathematical programming; NP-hard problem; Particle swarm optimization; Software algorithms; Flexible Job-shop; Hybrid particle swarm optimization; Scheduling; Simulation Software;
Conference_Titel :
Information and Automation (ICIA), 2010 IEEE International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-5701-4
DOI :
10.1109/ICINFA.2010.5512310
