Title :
A Novel Weight Design in Multi-objective Evolutionary Algorithm
Author :
Gu, Fang-Qing ; Liu, Hai-Lin
Author_Institution :
Fac. of Appl. Math., Guangdong Univ. of Technol., Guangzhou, China
Abstract :
This paper presents a method to improve the performance of MOEA/D. The idea is to approximate the Pareto front(PF) by using a linear interpolation of the non-dominant solutions. It propose a novel weight design method for multi-objective evolutionary algorithm. Even when the PF is complex, we can obtain the Pareto optimal solutions which are distributed uniformly over the PF. Some test functions are constructed to compare the performance of the proposed algorithm with that of MOEA/D. The results indicate that the proposed algorithm could significantly outperform MOEA/D on these test instances.
Keywords :
Pareto optimisation; evolutionary computation; interpolation; MOEA-D; Pareto front; linear interpolation; multiobjective evolutionary algorithm; Evolutionary algorithm; Multi-objective optimization; linear interpolation; uniformly distribution;
Conference_Titel :
Computational Intelligence and Security (CIS), 2010 International Conference on
Conference_Location :
Nanning
Print_ISBN :
978-1-4244-9114-8
Electronic_ISBN :
978-0-7695-4297-3
DOI :
10.1109/CIS.2010.37
