An interactive surrogate-based method for computationally expensive multiobjective optimisation. Issue 6 (3rd June 2019)

• Record Type: Journal Article
• Authors: Tabatabaei, Mohammad; Hartikainen, Markus; Sindhya, Karthik; Hakanen, Jussi; Miettinen, Kaisa
• Is Part Of: Journal of the Operational Research Society. Volume 70:Issue 6(2019)
• Page Start: 898
• Page End: 914
• Publication Date: 2019-06-03
• Subjects: Multiple criteria decision-making (MCDM) -- interactive methods -- computational cost -- black-box functions -- metamodeling techniques -- achievement scalarising function; Operations research -- Periodicals; 658.4034
• DOI: 10.1080/01605682.2018.1468860
• Languages: English
• ISSNs: 0160-5682

Abstract

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.