Titlebook: Success in Evolutionary Computation; Ang Yang,Yin Shan,Lam Thu Bui Book 2008 Springer-Verlag Berlin Heidelberg 2008 algorithm.algorithms.a

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978-3-642-09514-6Springer-Verlag Berlin Heidelberg 2008

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Success in Evolutionary Computation978-3-540-76286-7Series ISSN 1860-949X Series E-ISSN 1860-9503

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Privacy Protection with Genetic Algorithmsrce, health care, etc. We next propose a solution based on data aggregation, which is known to be NP-hard when applied to multivariate data. Due to this computational complexity, it is necessary to use heuristics to solve the problem. We propose the use of a Genetic Algorithm (GA) conveniently tuned up for tackling the problem properly.

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Ang Yang,Yin Shan,Lam Thu BuiReports recent research results on evolutionary computation in practice.Includes supplementary material:

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Survivable Network Design with an Evolution Strategyin-specific knowledge in the mutation operator and a repair heuristic raises the performance of an otherwise broadly applicable but less effective metaheuristic. Moreover, the results underline the important but so far often neglected potential of evolution strategies in combinatorial optimization.

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Evolving Cooperative Agents in Economy Market Using Genetic Algorithms to examine how well GA could perform against the IPD game strategies. We also explore the strategic interactions among the agents that represent firms in a coevolving population, and study the influence of the genetic operators on GA to evolve cooperative agents.

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Book 2008azing world around us. There can be little surprise, therefore, that Evolutionary Computation (EC), inspired by natural evolution, has been so successful in providing high quality solutions in a large number of domains. EC includes a number of techniques, such as Genetic Algorithms, Genetic Programm