Two-Phase Strategy Managing Insensitivity in Global Optimization

  • Jakub Sawicki
  • Maciej Smołka
  • Marcin Łoś
  • Robert Schaefer
  • Piotr Faliszewski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10199)

Abstract

Solving ill-posed continuous, global optimization problems remains challenging. For example, there are no well-established methods for handling objective insensitivity in the neighborhood of solutions, which appears in many important applications, e.g., in non-invasive tumor tissue diagnosis or geophysical exploration. The paper presents a complex metaheuristic that identifies regions of objective function’s insensitivity (plateaus). The strategy is composed of a multi-deme hierarchic memetic strategy coupled with random sample clustering, cluster integration, and special kind of multiwinner selection that allows to breed the demes and cover each plateau separately. We test the method on benchmarks with multiple non-convex plateaus and evaluate how well the plateaus are covered.

Keywords

Ill-posed global optimization problems New tournament-like selection Fitness insensitivity 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jakub Sawicki
    • 1
  • Maciej Smołka
    • 1
  • Marcin Łoś
    • 1
  • Robert Schaefer
    • 1
  • Piotr Faliszewski
    • 1
  1. 1.AGH University of Science and TechnologyKrakówPoland

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