Purshouse, R.C. and McAlister, J. (2013) Multi-objective optimisation for social cost benefit analysis: An allegory. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2013), 19-22 Mar 2013, Sheffield, UK. , 726 - 740.
Abstract
Social cost benefit analysis often involves consideration of non-monetary outcomes. Multi-objective optimisation is an appropriate method for handling problems of this type, but many decision-makers have a strong mistrust of the approach. Reflections by the authors on real experiences supporting decision-makers suggest that the key barriers to using multi-objective methods for social cost benefit analysis include: (i) the inadequacy of current social systems models for measuring the end benefits provided by a candidate solution; (ii) the lack of appropriate societal preference estimates for resolving the inherent trade-offs between objectives; and (iii) the lack of practical examples, case studies and guidance which demonstrate that the approach works well. © 2013 Springer-Verlag.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded according to the publisher's self-archiving policy. The original source of publication for this paper is: R.C. Purshouse et al. (Eds.): EMO 2013, LNCS 7811, pp. 726–740, 2013. The original publication is available at www.springerlink.com. |
Keywords: | multi-objective optimisation, decision support systems |
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: | Dr Robin C. Purshouse |
Date Deposited: | 01 Nov 2013 13:49 |
Last Modified: | 19 Dec 2022 13:25 |
Published Version: | http://dx.doi.org/10.1007/978-3-642-37140-0_54 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-642-37140-0_54 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:75436 |