Research on Agile Job-shop Scheduling Problem Based on Genetic Algorithm

Author

Li, Ye ; Tang, Da ; Chen, Yan

Author_Institution

Transp. Manage. Coll., Dalian Maritime Univ., Dalian, China

Volume

1

fYear

2009

fDate

22-24 May 2009

Firstpage

590

Lastpage

593

Abstract

A new genetic algorithm for solving the agile job shop scheduling is presented. The objective of this kind of job shop scheduling problem is minimizing the completion time of all the jobs, called the makespan, subject to the constraints. Initial population is generated randomly. Two-row chromosome structure is adopted based on working procedure and machine distribution. The relevant 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 8 working procedure and 5 machines. The feasibility of GA is showed by simulation result.

Keywords

genetic algorithms; job shop scheduling; minimisation; GA; agile job-shop scheduling problem; genetic algorithm; job completion time minimisation; local optimal solution; machine distribution; makespan minimisation; mutation operation; two-row chromosome structure; Algorithm design and analysis; Biological cells; Costs; Dynamic scheduling; Electronic commerce; Genetic algorithms; Heuristic algorithms; Integer linear programming; Job production systems; Job shop scheduling; agile job shop scheduling; genetic algorithm; machine distribution; two-row chromosome structure; working procedure;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic Commerce and Security, 2009. ISECS '09. Second International Symposium on

Conference_Location

Nanchang

Print_ISBN

978-0-7695-3643-9

Type

conf

DOI

10.1109/ISECS.2009.105

Filename

5209856