Solution Space Analysis and Feasible Genetic Algorithm for Assembly Job-shop Scheduling Problems

被引：2
|
作者：
Zhao, G. K. [1 ]
Wang, F. J. [1 ]
Liu, W. [1 ]
Lu, X. H. [1 ]
机构：
[1] Dalian Univ Technol, Minist Educ, Key Lab Precis & Nontradit Machining Technol, Dalian, Peoples R China
来源：
ADVANCES IN MATERIALS MANUFACTURING SCIENCE AND TECHNOLOGY XIII, VOL 1: ADVANCED MANUFACTURING TECHNOLOGY AND EQUIPMENT, AND MANUFACTURING SYSTEMS AND AUTOMATION | 2009年 / 626-627卷
关键词：
Assembly Job-shop Scheduling Problem; Feasible solution space; Fix operator; Feasible Genetic algorithm;
D O I：
10.4028/www.scientific.net/MSF.626-627.705
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The classical job-shop scheduling problems (JSP) become assembly job-shop scheduling problems (AJSP) if assembly constraints are attached to them. The entire solution space size and the feasible one of AJSP are analyzed and obtained by utilizing combinational mathematics It is proved that the feasible solution space takes extremely small portion of the entire one To minimize the makespan of AJSP, genetic algorithm searching in feasible solution space (FGA) is proposed and designed, and the search range of FGA is limited to feasible solution space. Finally, benchmarks tests and results are given which demonstrate the advantage and efficiency of FGA
引用
收藏
页码：705 / 710
页数：6
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