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
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;
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
DOI :
10.1109/CEC.2015.7257295