Scheduling for the Flexible Job-Shop Problem Based on Genetic Algorithm(GA)

被引：1

作者：

Fan, ShunCheng ^{[1
]}

Wang, JinFeng ^{[1
]}

机构：

[1] Hebei Univ Technol, Sch Mech Engn, Tianjin, Peoples R China

来源：

ADVANCED MATERIALS AND ENGINEERING MATERIALS, PTS 1 AND 2 | 2012年 / 457-458卷

关键词：

Job-shop Scheduling; Genetic algorithms; Selection; Crossover; Mutation;

D O I：

10.4028/www.scientific.net/AMR.457-458.616

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this paper, we analyze the characteristics of the flexible job-shop scheduling problem(FJSP). A novel genetic algorithm is elaborated to solve the FJSP. An improved chromosome representation is used to conveniently represent a solution of the FJSP. Initial population is generated randomly. The relevant selection, crossover and mutation operation is also designed. It jumped from the local optimal solution, and the search area of solution is improved. Finally, the algorithm is tested on instances of 4 jobs and 6 machines. Computational results prove the proposed genetic algorithm effective for solving the FJSP.

引用

页码：616 / 619

页数：4

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