Interactive multi-objective particle swarm optimisation using decision space interaction

Jan Hettenhausen, Andrew Lewis, Marcus Randall, Timoleon Kipouros

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

19 Citations (Scopus)
127 Downloads (Pure)

Abstract

The most common approach to decision making in multi-objective optimisation with metaheuristics is a posteriori preference articulation. Increased model complexity and a gradual increase of optimisation problems with three or more objectives have revived an interest in progressively interactive decision making, where a human decision maker interacts with the algorithm at regular intervals. This paper presents an interactive approach to multi-objective particle swarm optimisation (MOPSO) using a novel technique to preference articulation based on decision space interaction and visual preference articulation. The approach is tested on a 2D aerofoil design case study and comparisons are drawn to non-interactive MOPSO.

Original languageEnglish
Title of host publication2013 IEEE Congress on Evolutionary Computation, CEC 2013
Place of Publicationonline
PublisherWiley-IEEE Press
Pages3411-3418
Number of pages8
ISBN (Print)9781479904549
DOIs
Publication statusPublished - 2013
Event2013 IEEE Congress on Evolutionary Computation, CEC 2013 - Cancun, Cancun, Mexico
Duration: 20 Jun 201323 Jun 2013

Conference

Conference2013 IEEE Congress on Evolutionary Computation, CEC 2013
CountryMexico
CityCancun
Period20/06/1323/06/13

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  • Cite this

    Hettenhausen, J., Lewis, A., Randall, M., & Kipouros, T. (2013). Interactive multi-objective particle swarm optimisation using decision space interaction. In 2013 IEEE Congress on Evolutionary Computation, CEC 2013 (pp. 3411-3418). [6557988] online: Wiley-IEEE Press. https://doi.org/10.1109/CEC.2013.6557988