Titlebook: Marketinghandbuch Licensing; Brands und Lizenzthe Stefanie Brandt Book 2011 Gabler Verlag | Springer Fachmedien Wiesbaden GmbH, Wiesbaden 2

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gnment Algorithm, a Local search and an Estimation of Distribution Algorithm (EDA) with a reinforcement learning. We tested our approach with and without the learning effect. Our approach is efficient; we were able to manage a set of 10 parking lots over 120 days (problems with up to 7000 parking sl

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Axel Dammler representation of the Pareto front when the size of that set is larger than the archive bound. Furthermore, if the ranges of the PF of the sequence are not known a priori, no algorithm that certifies (using its own internal epsilon parameter ε.) that it maintains an epsilon-approximate set of the s

resistant

representation of the Pareto front when the size of that set is larger than the archive bound. Furthermore, if the ranges of the PF of the sequence are not known a priori, no algorithm that certifies (using its own internal epsilon parameter ε.) that it maintains an epsilon-approximate set of the s

conspicuous

Stefanie Brandt representation of the Pareto front when the size of that set is larger than the archive bound. Furthermore, if the ranges of the PF of the sequence are not known a priori, no algorithm that certifies (using its own internal epsilon parameter ε.) that it maintains an epsilon-approximate set of the s

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Stefanie Brandtt including machine using cost, machine maintenance cost and the maximization of the reconfiguration index based on the global capacity of reconfiguration of the system and the reconfigurability required by the product to manufacture. To solve the problem, an adapted version of the NSGA-II algorithm