Multi-objective Genetic Algorithm for Multistage-based Job Processing Schedules in FMS Environment

Author

Kim, KwanWoo ; Lee, DongJoo ; Jeong, In-Jae

Author_Institution

Hanyang Univ., Seoul

fYear

2007

fDate

May 30 2007-June 1 2007

Firstpage

1705

Lastpage

1709

Abstract

In this paper, we propose a multi-objective genetic algorithm for effectively solving multistage-based job processing schedules in FMS environment. The proposed method is random-weight approach to obtaining a variable search direction toward Pareto solution. The objectives are to minimize the makespan and the total flow time, simultaneously. The feasibility and adaptability of the proposed moGA are investigated through experimental results.

Keywords

Pareto analysis; flexible manufacturing systems; genetic algorithms; scheduling; FMS environment; Pareto solution; multiobjective genetic algorithm; multistage-based job processing schedules; random-weight approach; variable search direction; Automatic control; Automation; Flexible manufacturing systems; Genetic algorithms; Industrial engineering; Job shop scheduling; Mathematical programming; Optimal scheduling; Processor scheduling; Scheduling algorithm; FMS; Multi-objective genetic algorithm; Multistage-based job processing schedule; component;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation, 2007. ICCA 2007. IEEE International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4244-0817-7

Electronic_ISBN

978-1-4244-0818-4

Type

conf

DOI

10.1109/ICCA.2007.4376652

Filename

4376652