Enhancing Decision Space Diversity in Evolutionary Multiobjective Algorithms

  • Ofer M. Shir
  • Mike Preuss
  • Boris Naujoks
  • Michael Emmerich
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5467)


In multi-criterion optimization, Pareto-optimal solutions that appear very similar in the objective space may have very different pre-images. In many practical applications the decision makers, who select a solution or preferred region on the Pareto-front, may want to know different pre-images of the selected solutions. Especially, this will be the case when they would like to present alternative design candidates in later stages of a multidisciplinary design process.

In this paper we extend an existing CMA-ES niching framework, which has been previously applied successfully to multi-modal optimization, to the multi-criterion domain for boosting decision space diversity. At the same time, we introduce the concept of space aggregation for diversity maintenance in the aggregated spaces, i.e. search/decision and objective space. Empirical results on synthetic multi-modal bi-criteria test problems with known efficient sets and Pareto-fronts demonstrate that the diversity in the decision space can be significantly enhanced without hampering the convergence to a precise and diverse Pareto front approximation in the objective space of the original algorithm.


Pareto Front Multiobjective Optimization Objective Space Decision Space Evolutionary Multiobjective 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 Berlin Heidelberg 2009

Authors and Affiliations

  • Ofer M. Shir
    • 1
  • Mike Preuss
    • 2
  • Boris Naujoks
    • 2
  • Michael Emmerich
    • 3
  1. 1.Department of ChemistryPrinceton University Frick LabPrincetonUSA
  2. 2.Lehrstuhl für Algorithm EngineeringTechnische Universität DortmundDortmundGermany
  3. 3.Natural Computing GroupLIACS, Leiden UniversityLeidenThe Netherlands

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