Titlebook: Evolutionary Multi-Criterion Optimization; 8th International Co António Gaspar-Cunha,Carlos Henggeler Antunes,Carl Conference proceedings 2

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Using Indifference Information in Robust Ordinal Regressionence information one can represent more faithfully the DM’s preferences. Such information about indifference should narrow down the set of compatible value functions much more quickly than standard pairwise comparisons, and a first simple example at least indicates that this intuition seems to be correct.

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A Multi-objective Genetic Algorithm for Inferring Inter-criteria Parameters for Water Supply Consensndence with the preferences of the whole group (collective ranking). This paper shows how the inferring parameters model may be used to help the decision makers with different interest to iteratively reach an agreement on how to rank cities at a time, reflecting the preferences at the individual level and at the collective level.

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An Interactive Evolutionary Multiobjective Optimization Method: Interactive WASF-GAference point given. Interactive WASF-GA implies a much lower computational cost than the original WASF-GA because it generates a small number of solutions. This speeds up the convergence of the algorithm, making it suitable for many decision-making problems. Its efficiency and usefulness is demonstrated with a five-objective optimization problem.

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Conference proceedings 2015r?es, Portugal in March/April 2015. The 68 revised full papers presented together with 4 plenary talks were carefully reviewed and selected from 90 submissions. The EMO 2015 aims to continue these type of developments, being the papers presented focused in: theoretical aspects, algorithms developmen

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On the Behavior of Stochastic Local Search Within Parameter Dependent MOPssearch algorithms such as specialized evolutionary approaches. The discussion in particular indicates that it might be beneficial to integrate the set of external parameters directly into the search instead of computing projections of the solution sets separately by fixing the value of the external parameter.

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