MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework

  • Aymeric BlotEmail author
  • Holger H. HoosEmail author
  • Laetitia Jourdan
  • Marie-Éléonore Kessaci-Marmion
  • Heike Trautmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10079)


Automated algorithm configuration procedures play an increasingly important role in the development and application of algorithms for a wide range of computationally challenging problems. Until very recently, these configuration procedures were limited to optimising a single performance objective, such as the running time or solution quality achieved by the algorithm being configured. However, in many applications there is more than one performance objective of interest. This gives rise to the multi-objective automatic algorithm configuration problem, which involves finding a Pareto set of configurations of a given target algorithm that characterises trade-offs between multiple performance objectives. In this work, we introduce MO-ParamILS, a multi-objective extension of the state-of-the-art single-objective algorithm configuration framework ParamILS, and demonstrate that it produces good results on several challenging bi-objective algorithm configuration scenarios compared to a base-line obtained from using a state-of-the-art single-objective algorithm configurator.


Algorithm configuration Parameter tuning Multi-objective optimisation Local search algorithms 


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Aymeric Blot
    • 1
    • 2
    • 3
    Email author
  • Holger H. Hoos
    • 3
    Email author
  • Laetitia Jourdan
    • 1
  • Marie-Éléonore Kessaci-Marmion
    • 1
  • Heike Trautmann
    • 4
  1. 1.Université de Lille, Inria, CNRS, UMR 9189 – CRIStALLilleFrance
  2. 2.École Normale Supérieure de RennesRennesFrance
  3. 3.University of British ColumbiaVancouverCanada
  4. 4.University of MünsterMünsterGermany

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