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Titlebook: Computational Intelligence in Expensive Optimization Problems; Yoel Tenne,Chi-Keong Goh Book 2010 Springer-Verlag Berlin Heidelberg 2010 a

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31#
發(fā)表于 2025-3-27 00:15:56 | 只看該作者
Analysis of Approximation-Based Memetic Algorithms for Engineering Optimizationwith higher precision. The chapter proceeds to the formal analysis of approximation-based memetic algorithms, in which we investigate the effect of the local search operators on the global convergence properties of evolutionary algorithms viaMarkov chain theory, and also study the computational comp
32#
發(fā)表于 2025-3-27 01:54:14 | 只看該作者
33#
發(fā)表于 2025-3-27 06:59:52 | 只看該作者
Multi-objective Model Predictive Control Using Computational Intelligencems, the model predictive control has been developed along a similar idea to the above. This chapter discusses multi-objective model predictive control problems and proposes a method using computational intelligence such as support vector regression.
34#
發(fā)表于 2025-3-27 09:29:26 | 只看該作者
Differential Evolution with Scale Factor Local Search for Large Scale Problemsust algorithm for highly multivariate optimization, and the employment of the local search to the scale factor is beneficial in order to detect solutions with a high quality, convergence speed and algorithmic robustness.
35#
發(fā)表于 2025-3-27 15:12:30 | 只看該作者
36#
發(fā)表于 2025-3-27 21:15:52 | 只看該作者
37#
發(fā)表于 2025-3-28 01:52:34 | 只看該作者
38#
發(fā)表于 2025-3-28 04:48:07 | 只看該作者
39#
發(fā)表于 2025-3-28 06:32:49 | 只看該作者
Der Primat der Macht und der Ausnahmefall,nalyze different proposals currently available in the specialized literature to deal with expensive functions in evolutionary multi-objective optimization. Additionally, we review some real-world applications of these methods, which can be seen as case studies in which such techniques led to a subst
40#
發(fā)表于 2025-3-28 10:59:32 | 只看該作者
,Die Eind?mmung der Gewalt im Gro?raum,alues in place of metamodels. In addition, to profit of the availability of evaluation or parameterization models of lower fidelity and . cost and/or refinement methods, a multilevel search algorithm relying also on the use of metamodels is presented. The algorithm may optionally operate as hierarch
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