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Approximating the Knee of an MOP with Stochastic Search Algorithms

  • Oliver Schütze
  • Marco Laumanns
  • Carlos A. Coello Coello
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5199)

Abstract

In this paper we address the problem of approximating the ’knee’ of a bi-objective optimization problem with stochastic search algorithms. Knees or entire knee-regions are of particular interest since such solutions are often preferred by the decision makers in many applications. Here we propose and investigate two update strategies which can be used in combination with stochastic multi-objective search algorithms (e.g., evolutionary algorithms) and aim for the computation of the knee and the knee-region, respectively. Finally, we demonstrate the applicability of the approach on two examples.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Oliver Schütze
    • 1
  • Marco Laumanns
    • 2
  • Carlos A. Coello Coello
    • 1
  1. 1.CINVESTAV-IPN, Computer Science DepartmentMexico CityMexico
  2. 2.ETH Zurich, Institute for Operations ResearchZurichSwitzerland

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