DocumentCode
2227133
Title
A species based multiobjective evolutionary algorithm for multiobjective flow shop scheduling problem
Author
Wang, Hongfeng ; Fu, Yaping ; Huang, Min
Author_Institution
College of Information Science and Engineering, Northeastern University; State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University; Shenyang, P.R. China
fYear
2015
fDate
25-28 May 2015
Firstpage
3243
Lastpage
3247
Abstract
In recent years, multiobjective scheduling problems (MOSPs) have gained more and more concerns since many real-world applications always involve in multiple different objectives. In this paper, a multiobjective flow shop scheduling problem is investigated and a species based multiobjective evolutionary algorithm (MOEA), where a new multipopulation scheme is designed based on the mechanism of species that was used in EA for multimodal optimization problems, is proposed as its solution algorithm. Extensive experiments are carried out on a set of randomly-generated test problems in order to examine strongness and weakness of the performance of the proposed MOEA through comparing with two well-known MOEAs for addressing MOSPs.
Keywords
Algorithm design and analysis; Evolutionary computation; Job shop scheduling; Optimization; Sociology; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location
Sendai, Japan
Type
conf
DOI
10.1109/CEC.2015.7257295
Filename
7257295
Link To Document