Pareto Set and EMOA Behavior for Simple Multimodal Multiobjective Functions

  • Mike Preuss
  • Boris Naujoks
  • Günter Rudolph
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4193)


Recent research on evolutionary multiobjective optimization has mainly focused on Pareto fronts. However, we state that proper behavior of the utilized algorithms in decision/search space is necessary for obtaining good results if multimodal objective functions are concerned. Therefore, it makes sense to observe the development of Pareto sets as well. We do so on a simple, configurable problem, and detect interesting interactions between induced changes to the Pareto set and the ability of three optimization algorithms to keep track of Pareto fronts.


Pareto Front Decision Space Evolutionary Multiobjective Optimization Stochastic Enumeration 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 Berlin Heidelberg 2006

Authors and Affiliations

  • Mike Preuss
    • 1
  • Boris Naujoks
    • 1
  • Günter Rudolph
    • 1
  1. 1.Lehrstuhl für Algorithm EngineeringUniversität DortmundDortmundGermany

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