1997 | OriginalPaper | Buchkapitel
Reducing the Number of Criteria in Quasi-convex Multicriteria Optimization
verfasst von : Matthias Ehrgott, Stefan Nickel
Erschienen in: Operations Research Proceedings 1996
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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In this paper we prove a reduction result for the number of criteria in quasi-convex multiob- jective optimization. This result states that to decide whether a point x in the decision space is Pareto optimal it suffices to consider at most n + 1 criteria at a time, where n is the dimension of the decision space. The main theorem is based on a geometric characterization of Pareto, strict Pareto and weak Pareto solutions.