Titlebook: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V; Alexandru-Adrian Tantar,Emilia Tantar,Carlos

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rs to network managers new opportunities for deploying efficient security mechanisms. By means of applications and controller functionalities, SDN is able to provide a highly reactive network security monitoring, to perform comprehensive traffic analysis, and to enforce fine-grained dynamic access p

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advocated that many such operations can profit from cognitive learning based techniques that could drive many management or control operations. In that context a short overview of selected networking approaches like 3GPP Self Organizing Networks, Autonomic Network Management and Software-Defined Ne

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Conscious Consumption and Marketing Strategyexploratory tasks is analyzing Pareto landscapes, and we propose in both cases discrete graph-based reductions. Firstly, we introduce interactive navigation from a given suboptimal reference solution to Pareto efficient solution-points. The proposed traversal mechanism is based upon landscape improv

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all aim is to exploit this knowledge to give recommendations of the individually best suited algorithm for unseen optimization problems. Recent research revealed a high potential of this methodology in this respect based on a set of well-defined, computable features which only requires a quite small

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https://doi.org/10.1007/978-981-99-1191-2roughly investigate multi-objective optimization problems. These methods, however, suffer the drawback that they are restricted to low-dimensional problems, say .?≤?5 decision variables. The reason is that algorithms of this kind operate on a certain discretization on the entire search space resulti

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cal optimum. Iterated local search restarts the local search using perturbator operators, and the variable neighbourhood search alternates local search with various neighbourhoods. These two popular restarting techniques, or operators, evolve independently and are disconnected. We propose a metaheur

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Segmentation, Targeting, and Positioningically forms locally a manifold, specialized predictor-corrector methods that allow to follow the solution set from a given optimal point have proven to be very effective for such problems..In this work, we investigate two different possible choices for the predictor direction for bi-objective probl

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er contamination management needs solution of large sale simulation models as well as solution of complex optimal decision models. Often the best approach is to use linked simulation optimization models. However, the integration of optimization algorithm with large scale simulation of the physical p