 A note on robustness of the min-max solution to multi-objective linear programsErin K. Doolittle, Garrett M. Dranichak, Karyn Muir and Margaret M. Wiecek International Journal of Multicriteria Decision Making, 2016, vol. 6, issue 4, 343-365 Abstract: The challenge of using scalarising methods in multi-objective optimisation results from the choice of the method, which may not be apparent, and given that a method has been selected, from the choice of the values of the scalarising parameters. In general, these values may be unknown and the decision maker faces a difficult situation of making a choice possibly under a great deal of uncertainty. Due to its effectiveness, the robust optimisation approach of Ben-Tal and Nemirovski is applied to resolve the uncertainty carried in scalarised multi-objective linear programs (MOLPs). A robust counterpart is examined for six different scalarisations of the MOLP yielding robust (weakly) efficient solutions to the original MOLP. The study reveals that the min-max optimal solution emerges as a robust (weakly) efficient solution for five out of the six scalarisations. The implications of this result are also discussed. Keywords: robust optimisation; multi-objective linear programming; efficient solutions; robust counterpart; scalarisation; uncertainty; min-max solution; multi-objective optimisation. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmcdm:v:6:y:2016:i:4:p:343-365 Access Statistics for this article More articles in International Journal of Multicriteria Decision Making from Inderscience Enterprises Ltd |
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