Mathematical Model and Hybrid Particle Swarm Optimization for Flexible Job-Shop Scheduling Problem

被引：0
|
作者：
Zeng Ling-li [1 ]
Zou Feng-xing [1 ]
Xu Xiao-hong [1 ]
机构：
[1] Natl Univ Defense Technol, Coll Mechatron & Automat, Changsha 410073, Hunan, Peoples R China
来源：
WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09) | 2009年
关键词：
flexible job-shop scheduling; hybrid integer programming model; hybrid particle swarm optimization; crossover operator; mutation operator;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 simple particle swarm optimization(SPSO) algorithm and genetic algorithm(GA) is employed to solve this problem. Compared with SPSO algorithm, HPSO algorithm has a potential to reach a better optimum. The results of simulation indicate that, HPSO algorithm out performs SPSO algorithm on searching speed for global optimum and avoiding prematurity.
引用
收藏
页码：731 / 736
页数：6
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