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

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Conclusion: A New Bourgeois Habitus,n. When the optimisation problem experiences observational noise, there is also a trade-off with respect to accuracy refinement – as improving the estimate of a design’s performance typically is at the cost of additional function reevaluations. Empirically the most effective resampling approach deve

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Klemetti Näkkäläjärvi,Pekka Kauppalaindifference between real and fictitious alternatives. In particular, we allow the decision maker to suggest a new alternative that is different from the existing alternatives, but equally preferable. As shown by several experiments in psychology of the decisions, choosing between alternatives is di

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The Nature of Environmental Experience, supported for modifying the parameters of outranking methods in an iterative and interactive process. In this work, we provide an application of the procedure through evaluating eight municipal districts for Water Company to invest in projects of water supply. An inferring parameters model performe

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https://doi.org/10.1007/978-94-6209-944-9f forest at the minimum possible time, for rescuing support, fire detection, deforestation mitigation, among other important applications in the Amazon rain forest operational scenario. However, time is not the only criteria to be considered. Given that it is virtually impossible to recover a missin

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https://doi.org/10.1007/978-3-030-31818-5ion of the Pareto set for small-size enumerable instances. Our analysis provides further insights on the EMO search behavior and on the most important features that characterize the difficulty of an instance for this class of problems and algorithms.

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