Branke, Jürgen, Avigad, Gideon and Moshaiov, Amiram (2013) Multi-objective worst case optimization by means of evolutionary algorithms. Working Paper. Coventry, UK: WBS, University of Warwick. WBS working papers . (Unpublished)

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Abstract

Many real-world optimization problems are subject to uncertainty. A possible goal is then to find a solution which is robust in the sense that it has the best worst-case performance over all possible scenarios. However, if the problem also involves mul- tiple objectives, which scenario is “best” or “worst” depends on the user’s weighting of the different criteria, which is generally difficult to specify before alternatives are known. Evolutionary multi-objective optimization avoids this problem by searching for the whole front of Pareto optimal solutions. This paper extends the concept of Pareto dominance to worst case optimization problems and demonstrates how evolu- tionary algorithms can be used for worst case optimization in a multi-objective setting.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	H Social Sciences > HB Economic Theory Q Science > QA Mathematics
Divisions:	Faculty of Social Sciences > Warwick Business School > Operational Research & Management Sciences Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH):	Algorithms, Computer algorithms, Economics -- Mathematical models, Game theory
Series Name:	WBS working papers
Publisher:	WBS, University of Warwick
Place of Publication:	Coventry, UK
Official Date:	2013
Dates:	Date Event 2013 ["eprint_fieldopt_dates_date_type_available" not defined]
Number of Pages:	18
Status:	Not Peer Reviewed
Publication Status:	Unpublished

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