A Novel Weight Design in Multi-objective Evolutionary Algorithm

Authors:
Fang-Qing Gu;Hai-Lin Liu
Affiliations:
-;-
Venue:
CIS '10 Proceedings of the 2010 International Conference on Computational Intelligence and Security
Year:
2010

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A decomposition based estimation of distribution algorithm for multiobjective traveling salesman problems

Computers & Mathematics with Applications

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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.