APPLYING GENETIC LOCAL SEARCH ALGORITHM TO SOLVE THE JOB-SHOP SCHEDULING PROBLEM

被引：24
|
作者：
Zhu, Chuanjun [2 ]
Cao, Jing [2 ]
Hang, Yu [1 ]
Zhang, Chaoyong [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
[2] Hubei Univ Technol, Sch Mech Engn, Wuhan 430068, Peoples R China
来源：
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE | 2012年 / 19卷 / 09期
基金：
中国国家自然科学基金;
关键词：
Genetic Algorithms; Local Search Algorithms; Job-Shop Scheduling Problem; TUTORIAL SURVEY;
D O I：
10.1142/S2010194512008938
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper presents a genetic local search algorithm for the Job-Shop Scheduling problem, and the chromosome representation of the problem is based on the operation-based representation. In order to reduce the search space, schedules are constructed using a procedure that generates active schedules. After a schedule is obtained, a local search heuristic based on N6 neighborhood structure is applied to improve the solution. In order to avoid premature convergence of the conventional genetic algorithms (GA), the improved precedence operation crossover (IPOX) and approach of the generation alteration schema are proposed. The approach is tested on a set of standard instances taken from the literature. The computation results validate the effectiveness of the proposed algorithm.
引用
收藏
页码：341 / 349
页数：9
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