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An interactive surrogate-based method for computationally expensive multiobjective optimisation

Author

Listed:
  • Mohammad Tabatabaei
  • Markus Hartikainen
  • Karthik Sindhya
  • Jussi Hakanen
  • Kaisa Miettinen

Abstract

Many disciplines involve computationally expensive multiobjective optimisation problems. Surrogate-based methods are commonly used in the literature to alleviate the computational cost. In this paper, we develop an interactive surrogate-based method called SURROGATE-ASF to solve computationally expensive multiobjective optimisation problems. This method employs preference information of a decision-maker. Numerical results demonstrate that SURROGATE-ASF efficiently provides preferred solutions for a decision-maker. It can handle different types of problems involving for example multimodal objective functions and nonconvex and/or disconnected Pareto frontiers.

Suggested Citation

  • Mohammad Tabatabaei & Markus Hartikainen & Karthik Sindhya & Jussi Hakanen & Kaisa Miettinen, 2019. "An interactive surrogate-based method for computationally expensive multiobjective optimisation," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(6), pages 898-914, June.
    • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:6:p:898-914
    DOI: 10.1080/01605682.2018.1468860
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