A Hybrid Genetic Algorithm for Flexible Job-shop Scheduling Problem

被引：4
|
作者：
Wang Shuang-xi [1 ]
Zhang Chao-yong [1 ]
Jin Liang-liang [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Mech Sci & Engineer, Wuhan 430074, Peoples R China
来源：
ENGINEERING SOLUTIONS FOR MANUFACTURING PROCESSES IV, PTS 1 AND 2 | 2014年 / 889-890卷
关键词：
Flexible job-shop scheduling problem; Genetic algorithm; Initialization; Population improvement;
D O I：
10.4028/www.scientific.net/AMR.889-890.1179
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this paper, a hybrid genetic algorithm is presented for the flexible job-shop scheduling problem with makespan criterion. A new machine assignment strategy is proposed to improve the initial population. A modified coding scheme is presented, and a population improvement strategy is performed when the best solution of the population did not improve during some generations. This hybrid algorithm is tested on a series of benchmarks instances. Experimental results show that this hybrid algorithm is efficient and competitive compared to some existing methods.
引用
收藏
页码：1179 / 1184
页数：6
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