Multicriteria adaptive differential evolution for global numerical optimization

Date

2015-02-01

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

IOS Press

Type

Article

Peer reviewed

Yes

Abstract

Differential evolution (DE) has become a prevalent tool for global optimization problems since it was proposed in 1995. As usual, when applying DE to a specific problem, determining the most proper strategy and its associated parameter values is time-consuming. Moreover, to achieve good performance, DE often requires different strategies combined with different parameter values at different evolution stages. Thus integrating several strategies in one algorithm and determining the application rate of each strategy as well as its associated parameter values online become an ad-hoc research topic. This paper proposes a novel DE algorithm, called multicriteria adaptive DE (MADE), for global numerical optimization. In MADE, a multicriteria adaptation scheme is introduced to determine the trial vector generation strategies and the control parameters of each strategy are separately adjusted according to their most recently successful values. In the multicriteria adaptation scheme, the impacts of an operator application are measured in terms of exploitation and exploration capabilities and correspondingly a multi-objective decision procedure is introduced to aggregate the impacts. Thirty-eight scale numerical optimization problems with various characteristics and two real-world problems are applied to test the proposed idea. Results show that MADE is superior or competitive to six well-known DE variants in terms of solution quality and convergence performance.

Description

Keywords

Differential evolution, Adaptive algorithms, Evolutionary computation, multicriteria adaptive systems, Meta-heuristics, Optimisation

Citation

Cheng, J., Zhang, G., Caraffini, F. and Neri, F. (2015) Multicriteria adaptive differential evolution for global numerical optimization. Integrated Computer-Aided Engineering, 22 (2), pp. 103-107

Rights

Research Institute

Institute of Artificial Intelligence (IAI)