Compact differential evolution light: high performance despite limited memory requirement and modest computational overhead

Date

2012-09-01

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Springer US

Type

Article

Peer reviewed

Yes

Abstract

Compact algorithms are Estimation of Distribution Algorithms which mimic the behavior of population-based algorithms by means of a probabilistic representation of the population of candidate solutions. These algorithms have a similar behaviour with respect to population-based algorithms but require a much smaller memory. This feature is crucially important in some engineering applications, especially in robotics. A high performance compact algorithm is the compact Differential Evolution (cDE) algorithm. This paper proposes a novel implementation of cDE, namely compact Differential Evolution light (cDElight), to address not only the memory saving necessities but also real-time requirements. cDElight employs two novel algorithmic modifications for employing a smaller computational overhead without a performance loss, with respect to cDE. Numerical results, carried out on a broad set of test problems, show that cDElight, despite its minimal hardware requirements, does not deteriorate the performance of cDE and thus is competitive with other memory saving and population-based algorithms. An application in the field of mobile robotics highlights the usability and advantages of the proposed approach.

Description

Keywords

Differential Evolution, Optimisation

Citation

Iacca, G., Caraffini, F. and Neri, F. (2012) Compact differential evolution light: high performance despite limited memory requirement and modest computational overhead. Journal of Computer Science and Technology, 27 (5), pp.1056-1076

Rights

Research Institute

Institute of Artificial Intelligence (IAI)