Differential evolution for solving multiobjective optimization problems

Differential evolution for solving multiobjective optimization problems

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Article ID: iaor20071476
Country: Singapore
Volume: 21
Issue: 2
Start Page Number: 225
End Page Number: 240
Publication Date: Jun 2004
Journal: Asia-Pacific Journal of Operational Research
Authors: ,
Keywords: heuristics
Abstract:

The use of evolutionary strategies (ESs) to solve problems with multiple objectives [known as vector optimization problems (VOPs)] has attracted much attention recently. Being population-based approaches, ESs offer a means to find a set of Pareto-optimal solutions in a single run. Differential evolution (DE) is an ES that was developed to handle optimization problems over continuous domains. The objective of this paper is to introduce a novel Pareto-frontier differential evolution (PDE) algorithm to solve VOPs. The solutions provided by the proposed algorithm for two standard test problems outperform the ‘strength Pareto evolutionary algorithm’, one of the state-of-the-art evolutionary algorithms for solving VOPs.

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