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The Pareto-Box Problem for the Modelling of Evolutionary Multiobjective Optimization Algorithms

  • Mario Köppen
  • Raul Vicente-Garcia
  • Bertram Nickolay

Abstract

This paper presents the Pareto-Box problem for modelling evolutionary multi-objective search. The problem is to find the Pareto set of randomly selected points in the unit hypercube. While the Pareto set itself is only comprised of the point 0, this problem allows for a complete analysis of random search and demonstrates the fact that with increasing number of objectives, the probability of finding a dominated vector is decreasing exponentially. Since most nowadays evolutionary multi-objective optimization algorithms rely on the existence of dominated individuals, they show poor performance on this problem. However, the fuzzification of the Pareto-dominance is an example for an approach that does not need dominated individuals, thus it is able to solve the Pareto-Box problem even for a higher number of objectives.

Keywords

PARETO Front Multiobjective Optimization Random Search Unit Hypercube Evolutionary Multiobjective Optimization Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag/Wien 2005

Authors and Affiliations

  • Mario Köppen
    • 1
  • Raul Vicente-Garcia
    • 1
  • Bertram Nickolay
    • 1
  1. 1.Fraunhofer IPKBerlinGermany

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