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Automatically Configuring Multi-objective Local Search Using Multi-objective Optimisation

  • Aymeric Blot
  • Alexis Pernet
  • Laetitia Jourdan
  • Marie-Éléonore Kessaci-Marmion
  • Holger H. Hoos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10173)

Abstract

Automatic algorithm configuration (AAC) is becoming an increasingly crucial component in the design of high-performance solvers for many challenging combinatorial optimisation problems. This raises the question how to most effectively leverage AAC in the context of building or optimising multi-objective optimisation algorithms, and specifically, multi-objective local search procedures. Because the performance of multi-objective optimisation algorithms cannot be fully characterised by a single performance indicator, we believe that AAC for multi-objective local search should make use of multi-objective configuration procedures. We test this belief by using MO-ParamILS to automatically configure a highly parametric iterated local search framework for the classical and widely studied bi-objective permutation flowshop problem. To the best of our knowledge, this is the first time a multi-objective optimisation algorithm is automatically configured in a multi-objective fashion, and our results demonstrate that this approach can produce very good results as well as interesting insights into the efficacy of various strategies and components of a flexible multi-objective local search framework.

Keywords

Algorithm configuration Multi-objective optimisation Local search Permutation flowshop scheduling 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Aymeric Blot
    • 1
  • Alexis Pernet
    • 1
  • Laetitia Jourdan
    • 1
  • Marie-Éléonore Kessaci-Marmion
    • 1
  • Holger H. Hoos
    • 2
    • 3
  1. 1.Université de Lille, Inria, CNRS, UMR 9189 – CRIStALLilleFrance
  2. 2.University of British ColumbiaVancouverCanada
  3. 3.Universiteit LeidenLeidenThe Netherlands

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