A new approach to target region based multiobjective evolutionary algorithms

Yali Wang, Longmei Li, Kaifeng Yang, Michael T.M. Emmerich

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

10 Citations (Scopus)

Abstract

In this paper, a target region based multiobjective evolutionary algorithm framework is proposed to incorporate preference into the optimization process. It aims at finding a more fine-grained resolution of a target region without exploring the whole set of Pareto optimal solutions. It can guide the search towards the regions on the Pareto Front which are of real interest to the decision maker. The algorithm framework has been combined with SMS-EMOA, R2-EMOA, NSGA-II to form three target region based multiobjective evolutionary algorithms: T-SMS-EMOA, T-R2-EMOA and T-NSGA-II. In these algorithms, three ranking criteria are applied to achieve a well-converged and well-distributed set of Pareto optimal solutions in the target region. The three criteria are: 1. Non-dominated sorting; 2. indicators (hypervolume or R2 indicator) or crowding distance in the new coordinate space (i.e. target region) after coordinate transformation; 3. the Chebyshev distance to the target region. Rectangular and spherical target regions have been tested on some benchmark problems, including continuous problems and discrete problems. Experimental results show that new algorithms can handle the preference information very well and find an adequate set of Pareto-optimal solutions in the preferred regions quickly. Moreover, the proposed algorithms have been enhanced to support multiple target regions and preference information based on a target point or multiple target points. Some results of enhanced algorithms are presented.

Original languageEnglish
Title of host publication2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1757-1764
Number of pages8
ISBN (Electronic)9781509046010
DOIs
Publication statusPublished - 5 Jul 2017
Event2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Donostia-San Sebastian, Spain
Duration: 5 Jun 20178 Jun 2017

Publication series

Name2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings

Conference

Conference2017 IEEE Congress on Evolutionary Computation, CEC 2017
Country/TerritorySpain
CityDonostia-San Sebastian
Period05.06.201708.06.2017

Keywords

  • Coordinate transformation
  • Evolutionary algorithms
  • Multiobjective optimization
  • Preference
  • Target region

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