Titlebook: Evolutionary Computation in Practice; Tina Yu,Lawrence Davis,Rajkumar Roy Book 2008 Springer-Verlag Berlin Heidelberg 2008 Evolutionary Al

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An Introduction to Evolutionary Computation in Practice,ly discussed in a typical EC course curriculum. Meanwhile, although the values of applied research are acknowledged by most EC technologists, the perception seems to be very narrow: success stories boost morale and high profile applications can help to secure funding for future research and can help to attract high caliber students.

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Multi-Level Decomposition for Tractability in Structural Design Optimization,oblems that have both large design spaces and time-intensive analyses, rendering them intractable to traditional methods. In an example problem, a set of loosely coupled optimization agents is shown to reduce dramatically the computing time needed to find good solutions to such problems. The savings

BILIO

carotid-bruit

Evolving Microstructured Optical Fibres,of holes. This chapter presents a genetic algorithm which uses an embryogeny representation, or a growth phase, to convert a design from its genetic encoding (genotype) to the microstructured fibre (phenotype). The work demonstrates the application of variable-complexity, evolutionary design approac

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Optimization of Store Performance Using Personalized Pricing,he store performance is optimized using Monte-Carlo simulations and evolutionary computation. The results showed that individual pricing outperforms the traditional product-centered approach significantly. We believe that the successful implementation of the proposed research will impact the grocery

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A Computational Intelligence Approach to Railway Track Intervention Planning,eterioration patterns of sections of track are first analyzed. A Rival Penalized Competitive Learning algorithm is then used to determine possible failure types. We have devised a generalized two stage evolutionary algorithm to produce curve functions for this purpose. The approach is illustrated us

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erythema