Wang, R., Purshouse, R.C., Giagkiozis, I. et al. (1 more author) (2014) The iPICEA-g: a new hybrid evolutionary multi-criteria decision making approach using the brushing technique. European Journal of Operational Research, 243 (2). 442 - 453. ISSN 0377-2217
Abstract
Various preference-based multi-objective evolutionary algorithms have been developed to help a decision-maker search for his/her preferred solutions to multi-objective problems. In most of the existing approaches the decision-maker preferences are formulated either by mathematical expressions such as the utility function or simply by numerical values such as aspiration levels and weights. However, in some sense a decision-maker may find it easier to specify preferences visually by drawing rather than using numbers. This paper introduces such a method, namely, the brushing technique. Using this technique the decision-maker can specify his/her preferences easily by drawing in the objective space. Combining the brushing technique with one existing algorithm PICEA-g, we present a novel approach named iPICEA-g for an interactive decision-making. The performance of iPICEA-g is tested on a set of benchmark problems and is shown to be good.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 Elsevier. This is an author produced version of a paper subsequently published in European Journal of Operational Research. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Preference articulation; Decision making; Multi-objective optimization; Evolutionary algorithms |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Oct 2015 16:00 |
Last Modified: | 17 Nov 2015 19:07 |
Published Version: | http://dx.doi.org/10.1016/j.ejor.2014.10.056 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.ejor.2014.10.056 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:86088 |