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A Study on Population’s Diversity for Dynamic Environments

  • Anabela Simões
  • Rui Carvalho
  • João Campos
  • Ernesto Costa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6593)

Abstract

The use of mechanisms that generate and maintain diversity in the population was always seen as fundamental to help Evolutionary Algorithms to achieve better performances when dealing with dynamic environments. In the last years, several studies showed that this is not always true and, in some situations, too much diversity can hinder the performance of the Evolutionary Algorithms dealing with dynamic environments. In order to have more insight about this important issue, we tested the performance of four types of Evolutionary Algorithms using different methods for promoting diversity. All the algorithms were tested in cyclic and random dynamic environments using two different benchmark problems. We measured the diversity of the population and the performances obtained by the algorithms and important conclusions were obtained.

Keywords

Evolutionary Computation Dynamic Optimization Diversity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Anabela Simões
    • 1
    • 2
  • Rui Carvalho
    • 1
  • João Campos
    • 1
  • Ernesto Costa
    • 2
  1. 1.Coimbra Institute of EngineeringPolytechnic Institute of CoimbraCoimbraPortugal
  2. 2.Centre for Informatics and SystemsUniversity of CoimbraCoimbraPortugal

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