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: | Sarker Ruhul, Abbass Hussein A. |
Keywords: | heuristics |
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.