On multi-objective efficient global optimization via universal Kriging surrogate model

Pramudita Satria Palar, Koji Shimoyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper investigates the capability of universal Kriging (UK), or Kriging with a trend, approximator enhanced with the efficient global optimization (EGO) method to solve expensive multi-objective design optimization problem. Engineering optimization problems typically can be well described with smooth and polynomial-like behavior, which is the main rationale to apply UK over the ordinary Kriging (OK) as the approximator. The UK with orthogonal polynomials and basis selection based on least-angle-regression is utilized for this purpose. Results and demonstration on three synthetic functions using expected hypervolume improvement (EHVI) and Euclidean-based expected improvement (EEI) criterions show the increased quality of the optimized non-dominated solutions when UK is coupled with EHVI criterion. On the other hand, the coupling of UK with EEI does not lead to any improvement and might produce an adverse effect. We also observed that the use of UK mainly improves the proximity to the true Pareto front, with smaller but notable effect on the diversity of the solutions when EHVI is applied as the criterion. As expected, optimization using the UK shows the greatest improvement if all objective functions can be sufficiently approximated by the UK. Based on the results, we suggest that coupling of UK and EHVI criterion is a potential approach to solve the expensive real-world multi-objective optimization problem.

Original languageEnglish
Title of host publication2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages621-628
Number of pages8
ISBN (Electronic)9781509046010
DOIs
Publication statusPublished - 2017 Jul 5
Event2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Donostia-San Sebastian, Spain
Duration: 2017 Jun 52017 Jun 8

Publication series

Name2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings

Other

Other2017 IEEE Congress on Evolutionary Computation, CEC 2017
CountrySpain
CityDonostia-San Sebastian
Period17/6/517/6/8

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Signal Processing

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