Titlebook: Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing; Hime Aguiar e Oliveira Junior,Lester Ingber,M

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Unconstrained Optimizationconstrained problems will be presented, aiming to show the readers how to benefit from using the method in their own tasks. Initially, an overview of Fuzzy ASA will be shown and, after that, many cost functions will be defined and minimized with ASA and Fuzzy ASA, being the results compared in each

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Statistical Estimation and Global Optimizations is the so-called Maximum Likelihood Estimation Method, based upon the premise that the best estimative for the set of parameters corresponding to the actual PDF of the population under study is that one maximizing the likelihood function, relative to that set of sample points. To find global maxim

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Nonlinear Equation Solvingl problem is transformed into a global optimization one by synthesizing objective functions whose global minima, if any, are also solutions to the original system. The global minimization process is triggered from different starting points so as to find as many solutions as possible. To demonstrate

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Space-Filling Curves and Fuzzy ASAing curves and fuzzy adaptive simulated annealing, aiming at finding global minima of real-valued (possibly multimodal) functions that are not necessarily well behaved, that is, are not required to be differentiable, continuous, or even satisfying Lipschitz conditions. The overall idea is as follows

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