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Titlebook: Evolutionary Algorithms; Lawrence David Davis,Kenneth Jong,L. Darrell Whitl Book 1999 Springer-Verlag New York,Inc. 1999 control.evolution

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Applying Genetic Algorithms to Real-World Problems,uperiority of crossover-based search over a classic Branch & Bound, the second shows the superiority of the . over standard .s applied to grouping problems, and the third illustrates the kind of industrial applications GAS can be called upon to solve.
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Genetic Algorithms and the Design of Experiments,d demonstrate the fact that not all epistasis in necessarily harmful. Using ED concepts we are also able to show that in general it is not possible to determine a . that a given problem instance is likely to be hard or easy to optimize by means of a GA Finally, we show how the concept of an . ED can
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Efficient Parameter Optimization Based on Combination of Direct Global and Local Search Methods,ed 2-phase optimization strategy has been proven to be both powerful and efficient. The excellent heuristic properties of this hybrid method allows to use it as the basic component of a multiple-stage optimization strategy. The goal of multiple-stage optimization is to perform a systematic analysis
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Lawrence David Davis,Kenneth Jong,L. Darrell Whitl
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https://doi.org/10.1007/978-3-642-47867-3f high fitness solutions that best accounts for biological variability. The search space was high dimensional (> 100) and each function evaluation required from one minute to several hours of CPU time on high performance computers. Using this model and our goals as an example, we will: 1) review the
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https://doi.org/10.1007/978-3-663-04828-2uperiority of crossover-based search over a classic Branch & Bound, the second shows the superiority of the . over standard .s applied to grouping problems, and the third illustrates the kind of industrial applications GAS can be called upon to solve.
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