Titlebook: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation III; Oliver Schuetze,Carlos A. Coello Coello,Pi

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. points. It is a common performance indicator for judging the quality of Pareto front approximations. As it does not require a-priori knowledge of the Pareto front it can also be used in a straightforward manner for guiding the search for finite approximations to the Pareto front in multi-objective

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ctive optimisation. The algorithm takes inspiration from the slime mould ., an amoeboid organism that in its plasmodium state extends and optimizes a net of veins looking for food. The algorithm is here used to solve multi-objective Traveling Salesman and Vehicle Routing Problems selected as represe

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Sucking Pests of Vegetable Cropsle objectives within the limits of certain constraints, yet there still exists some uncertainty about finding a generally trustworthy method that can consistently find solutions which are really close to desired objectives in all situations. In this study, a combined Pareto multi-objective different

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The Morphology of the Sugar Cane Plant,utionary multiobjective optimization. Recently, a new partitioning mechanism, the . (PSA), has been introduced. It was shown that this partitioning allows for the selection of a well-diversified set out of an arbitrary given set, while maintaining low computational cost. When embedded into an evolut

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