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Titlebook: Integral Global Optimization; Theory, Implementati Soo Hong Chew,Quan Zheng Book 1988 Springer-Verlag Berlin Heidelberg 1988 algorithms.glo

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https://doi.org/10.1007/978-3-642-46623-6algorithms; global optimization; integration; optimization; strategy
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Book 1988tions were developed for a class of noncontinuous functions characterized by their having level sets that are robust. The integration-based approach contrasts with existing approaches which require some degree of convexity or differentiability of the objective function. Some computational results on a personal computer are presented.
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Preliminary,Suppose X is a Hausdorff topological space, f a real valued function on X and S a closed subset of X. The problem is to find the infimum of f over S:.and the set of global minima . that solve this problem. We begin with the following assumptions: Assumption A1: f is continuous on S.
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Applications,In this section, we present examples for the automatic design of optical thin films and optimal equalizer design for transmission lines to illustrate actual applications of global optimization to unconstrained problems.
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Lecture Notes in Economics and Mathematical Systemshttp://image.papertrans.cn/i/image/468313.jpg
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Integral Characterizations of Global Optimality,st all such attempts are of a local nature. Even then, they have tended to require several levels of differentiability unless some convexity hypotheses are imposed. The search for necessary and sufficient conditions for global optimality without requiring any convexity is an important and needed endeavor.
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Monte Carlo Implementation, is in general more involved. But accuracy is not generally required from the earlier discussion of the influence of errors. This suggests that a Monte Carlo based technique of finding the global minimum will be appropriate.
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