Interactive multi-objective particle swarm optimization with heatmap-visualization-based user interface

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Title Interactive multi-objective particle swarm optimization with heatmap-visualization-based user interface
Author Hettenhausen, Jan; Lewis, Andrew; Mostaghim, Sanaz
Journal Name Engineering Optimization
Year Published 2010
Place of publication United Kingdom
Publisher Taylor & Francis
Abstract This article introduces an interactive Multi-Objective Particle Swarm Optimization (MOPSO) method that allows a human decision maker to guide the optimization process based on domain-specific knowledge and problem-specific preferences. This article also presents a novel graphical user interface based on heatmap visualization which, combined with the algorithm, greatly reduces the workload on the user, thereby decreasing unwanted side effects caused by human fatigue. The method was evaluated on a set of standard test problems and the results were compared to those of a non-interactive MOPSO method. To simulate domain-specific preferences and knowledge, the decision maker was instructed to focus the search on a specific region of the Pareto-front. The results demonstrate that the proposed method was able to obtain better solutions than the non-interactive MOPSO method in terms of convergence towards the true Pareto-front and the number and spread of focused solutions.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1080/03052150903042632
Copyright Statement Copyright 2010 Taylor & Francis. This is an electronic version of an article published in Engineering Optimization, Volume 42, Issue 2 February 2010 , pages 119 - 139 . Engineering Optimization is available online at: http://www.informaworld.com with the open URL of your article.
Volume 42
Issue Number 2
Page from 119
Page to 139
ISSN 0305-215X
Date Accessioned 2010-01-19
Date Available 2013-03-19T22:47:58Z
Language en_US
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Computer Software; Optimisation
URI http://hdl.handle.net/10072/33179
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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