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Journal of Computer Science and Technology

, Volume 27, Issue 5, pp 1056–1076 | Cite as

Compact Differential Evolution Light: High Performance Despite Limited Memory Requirement and Modest Computational Overhead

  • Giovanni Iacca
  • Fabio Caraffini
  • Ferrante Neri
Regular Paper

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.

Keywords

differential evolution compact optimization real-time optimization 

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Copyright information

© Springer Science+Business Media New York & Science Press, China 2012

Authors and Affiliations

  • Giovanni Iacca
    • 1
  • Fabio Caraffini
    • 1
  • Ferrante Neri
    • 1
  1. 1.Department of Mathematical Information TechnologyUniversity of JyväskyläJyväskyläFinland

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