Apply MGA to Multi-objective Flexible Job Shop Scheduling Problem

Author

Yang, Xiaomei ; Zeng, Jianchao ; Liang, Jiye

Author_Institution

Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China

Volume

3

fYear

2009

Firstpage

436

Lastpage

439

Abstract

Through describing the characteristic of current genetic scheduling algorithm, a modified genetic scheduling algorithm (MGA) is proposed according to multi-objective Flexible Job Shop Scheduling Problem. This algorithm introduces a specific representation to reduce the solving space. It obtains the reasonable individuals by the selected principle and weakest link effect. Based on analyzing the benchmark of Flexible Job Shop Scheduling Problem, the computation results validate the effectivity of the proposed algorithm.

Keywords

flexible manufacturing systems; genetic algorithms; job shop scheduling; genetic algorithm; modified genetic scheduling algorithm; multi-objective flexible job shop scheduling problem; Algorithm design and analysis; Competitive intelligence; Genetic algorithms; Industrial engineering; Information management; Innovation management; Intelligent systems; Job shop scheduling; Laboratories; Scheduling algorithm; Flexible Job Shop Scheduling Problem; Genetic Algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Management, Innovation Management and Industrial Engineering, 2009 International Conference on

Print_ISBN

978-0-7695-3876-1

Type

conf

DOI

10.1109/ICIII.2009.414

Filename

5369154