Interactive Evolutionary Multiple Objective Optimization for Group Decision Incorporating Value-based Preference Disaggregation MethodsReportar como inadecuado




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Group Decision and Negotiation

, Volume 26, Issue 4, pp 693–728

First Online: 09 August 2016DOI: 10.1007-s10726-016-9506-6

Cite this article as: Kadziński, M. & Tomczyk, M.K. Group Decis Negot 2017 26: 693. doi:10.1007-s10726-016-9506-6

Abstract

We present a set of interactive evolutionary multiple objective optimization MOO methods, called NEMO-GROUP. All proposed approaches incorporate pairwise comparisons of several decision makers DMs into the evolutionary search, though evaluating the suitability of solutions for inclusion in the next population in different ways. The performance of algorithms is quantified with various convergence factors derived from the extensive computational tests on a set of benchmark problems. The best individuals and complete populations of solutions constructed by the proposed approaches are evaluated in terms of both utilitarian and egalitarian group value functions for different numbers of DMs. Our results indicate that more promising directions for optimization can be discovered when exploiting the set of value functions compatible with the DMs’ preferences rather than selecting a single representative value function for each DM or all DMs considered jointly. We demonstrate that NEMO-GROUP is flexible enough to account for the weights assigned to the DMs. We also show that by appropriately adjusting the elicitation interval and starting generation of the elicitation, one could significantly decrease the number of pairwise comparisons the DMs need to perform to construct a satisfactory solution.

KeywordsEvolutionary multiple objective optimization Interactive method Group decision Additive value function Preference disaggregation NEMO This paper significantly extends our work presented at the 2015 Group Decision and Negotiation International Conference GDN 2015 in Warsaw, Poland June 22–26, 2015.





Autor: Miłosz Kadziński - Michał K. Tomczyk

Fuente: https://link.springer.com/







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