SO-I: a surrogate model algorithm for expensive nonlinear integer programming problems including global optimization applications
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Publication:743971
DOI10.1007/s10898-013-0101-yzbMath1305.90305OpenAlexW2090517984MaRDI QIDQ743971
Christine A. Shoemaker, Juliane Müller, Robert Piché
Publication date: 2 October 2014
Published in: Journal of Global Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10898-013-0101-y
global optimizationradial basis functionsnonlinearlinearnonconvexresponse surfacesurrogate modelmultimodalderivative-freecomputationally expensiveinteger optimization
Related Items (14)
MISO: mixed-integer surrogate optimization framework ⋮ Surrogate‐based methods for black‐box optimization ⋮ Kriging-assisted teaching-learning-based optimization (KTLBO) to solve computationally expensive constrained problems ⋮ Derivative-free methods for mixed-integer nonsmooth constrained optimization ⋮ GOSAC: global optimization with surrogate approximation of constraints ⋮ Multi objective optimization of computationally expensive multi-modal functions with RBF surrogates and multi-rule selection ⋮ SOCEMO: Surrogate Optimization of Computationally Expensive Multiobjective Problems ⋮ An algorithmic framework based on primitive directions and nonmonotone line searches for black-box optimization problems with integer variables ⋮ Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints ⋮ The Mesh Adaptive Direct Search Algorithm for Granular and Discrete Variables ⋮ A method for convex black-box integer global optimization ⋮ Surrogate optimization of deep neural networks for groundwater predictions ⋮ Derivative-free optimization methods ⋮ Review and comparison of algorithms and software for mixed-integer derivative-free optimization
Uses Software
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