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Titlebook: Metaheuristics; 14th International C Luca Di Gaspero,Paola Festa,Mario Pavone Conference proceedings 2023 The Editor(s) (if applicable) and

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楼主: 螺丝刀
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Carolina Crespi,Rocco A. Scollo,Georgia Fargetta,Mario Pavoneko groß gewesen wäre, dass diese Arbeit mit viel Aufwand nur das herausbekommen hätte, was schon längst dem Status quo entspricht (vgl. Hopf 1996, S. 19). Drittens, weil eine Vollerhebung der .-Anstalten durchgeführt wurde. Diese war zwar nicht rein quantifizierend angelegt — und wurde auch nicht so
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N. Aslimani,E-G. Talbi,R. Ellaiarden zunächst die Genauigkeit und Verzerrung der Gewinnprognosen sowie deren Vergleich zur naiven Random Walk-Prognose in Abhängigkeit vom Prognosehorizont, vom Kalenderjahr der Prognoseerstellung, vom Fiskaljahr, von der Richtung der vergangenen Gewinnentwicklung sowie vom Industriesektor dargestel
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,New Neighborhood Strategies for the Bi-objective Vehicle Routing Problem with Time Windows,e two neighborhood strategies to improve an existing LS, efficient on the single-objective VRPTW. First, we propose a new strategy to explore the neighborhood of a solution. Second, we propose a new strategy for pruning the solution neighborhood that takes into account the second criterion of our bV
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,Tabu Search with Multiple Decision Levels for Solving Heterogeneous Fleet Pollution Routing Problemhe greatest impact on health are measured: carbon dioxide (.), nitrogen dioxide (.) and carbon monoxide (.). For its solution, a Tabu Search metaheuristic is proposed with different decision levels: node sequence, assigned speeds and vehicles used, from different neighborhood structures. Finally, th
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,On Optimizing the Structure of Neural Networks Through a Compact Codification of Their Architectureake this continuous optimizer compatible with neural network design. This method, which is of general application, i.e., not linked to TLBO, can represent different network architectures with a plain vector of real values. A compatible objective function that links the optimizer and the representati
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Neural Architecture Search Using Differential Evolution in MAML Framework for Few-Shot Classificatiesults reveal that MAML-NAS results in better or at least comparable accuracy values for both of the datasets in all settings. More importantly, this performance is achieved by much simpler architectures, that is architectures requiring less floating-point operations.
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Neural Architecture Search Using Metaheuristics for Automated Cell Segmentation, and Local Search (LS), and the generated networks have been tested on Optofil and Cell Nuclei data sets. When the results are examined, it is seen that the networks produced by the heuristic methods improve the performance of the U-Net structure in terms of both segmentation performance and computa
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