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C.: PDE: A Pareto-frontier differential evolution approach for multi-objective optimization problems
| Venue: | In: Proceedings of the 2001 Congress on Evolutionary Computation – CEC 2001. Volume |
| Citations: | 53 - 3 self |
BibTeX
@INPROCEEDINGS{Abbass_c.:pde:,
author = {Hussein A. Abbass and Ruhul Sarker and Charles Newton},
title = {C.: PDE: A Pareto-frontier differential evolution approach for multi-objective optimization problems},
booktitle = {In: Proceedings of the 2001 Congress on Evolutionary Computation – CEC 2001. Volume},
year = {},
pages = {971--978}
}
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Abstract
The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Multi-objective Optimization Problems (MOPs)) has attracted much attention recently. Being popula-tion based approaches, EAs offer a means to find a group of pareto-optimal solutions in a single run. Differential Evolution (DE) is an EA 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 MOPs. 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 algorithm for solving MOPs. 1
Keyphrases
multi-objective optimization problem pareto-frontier differential evolution approach pareto-optimal solution continuous domain novel pareto frontier differential evolution multiple objective differential evolution optimization problem single run standard test problem state-of-the-art evolutionary algorithm strength pareto evolutionary algorithm evolutionary algorithm much attention
