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Bayesian methods in global optimization
Journal of Global Optimization, 1991The paper reviews methods which have been proposed for solving global optimization problems in the framework of the Bayesian paradigm. Three main approaches are singled out. In the first approach, called the Random Function Approach, methods are based on the idea of introducing a probabilistic model for the objective function in the form of a random ...
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Global optimization of Hölder functions
Journal of Global Optimization, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Éric Gourdin +2 more
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On a Method of Global Optimization
2003The usual optimization problem, in eventually introducing some further new variables, may be put in the following form: Optimization Problem O.
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Global Optimization on Funneling Landscapes
Journal of Global Optimization, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Global Optimization by Monotonic Transformation
Computational Optimization and Applications, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Global Optimization in the COCONUT Project
2004In this article, a solver platform for global optimization is presented, as it is developed in the COCONUT project. After a short introduction, a short description is given of the basic algorithmic concept and of all relevant components, the strategy engine, inference engines, and the remaining modules. A compact description of the search graph and its
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Non-convex quadratic minimization problems with quadratic constraints: global optimality conditions
Mathematical Programming, 2006V Jeyakumar, A M Rubinov, Jeyakumar V
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Optimality conditions for global optimization (II)
Acta Mathematicae Applicatae Sinica, 1985Zheng Quan
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