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ABSTRACT

Hierarchically organised evolution strategies have been seen to be able to successfully adapt step lengths where mutative self-adaptation fails. However, the computational costs of such strategies are high due to the need to evolve several subpopulations in isolation, and their performance depends crucially on the length of the isolation periods. This paper proposes a novel approach to adapting the length of the isolation periods that is found to robustly generate good settings across a range of test functions.

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INDEX TERMS

Primary Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization
          Subjects: Unconstrained optimization

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search

General Terms:
Algorithms, Performance

Keywords:
hierarchically organised evolution strategies, reproductive isolation, step length adaptation