Research on job-shop scheduling problem based on Self-Adaptation Genetic Algorithm

Author

Hongyan, Xie ; Hong, Huo

Author_Institution

Sch. of Manage., Harbin Univ. of Commerce, Harbin, China

Volume

2

fYear

2010

fDate

9-10 Jan. 2010

Firstpage

940

Lastpage

943

Abstract

The multi-objective optimization problem in flexible job-shop scheduling was discussed. According to the characteristics of flexible job-shop scheduling, a new self-adaptive genetic algorithm was proposed, and the model of Multi-Objective Flexible Job-shop Scheduling (MOFJS) was set up. At last, by programming with Matlab and Visual C++, the algorithm was applied to solve the MOFJS problem in Chinese automobile manufacturing enterprises, and the optimization scheduling solution was obtained. The simulation results show that the proposed algorithm is feasible and effective for MOFJS.

Keywords

automobile industry; automobile manufacture; genetic algorithms; job shop scheduling; Chinese automobile manufacturing enterprises; MOFJS; Matlab; Visual C++; job-shop scheduling problem; multiobjective flexible job-shop scheduling; multiobjective optimization problem; optimization scheduling solution; self-adaptation genetic algorithm; self-adaptive genetic algorithm; Automobile manufacture; Biological cells; Business; Concrete; Genetic algorithms; Gradient methods; Job shop scheduling; Mathematical model; Optimization methods; Scheduling algorithm; Flexible Job-shop Scheduling; Multi-objective Optimization; Self-Adaptive Genetic Algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Logistics Systems and Intelligent Management, 2010 International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4244-7331-1

Type

conf

DOI

10.1109/ICLSIM.2010.5461042

Filename

5461042