SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems

This paper introduces a surrogate model based algorithm for computationally expensive mixed-integer black-box global optimization problems with both binary and non-binary integer variables that may have computationally expensive constraints. The goal is to find accurate solutions with relatively few...

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Veröffentlicht in:	Computers & operations research Jg. 40; H. 5; S. 1383 - 1400
Hauptverfasser:	Müller, Juliane, Shoemaker, Christine A., Piché, Robert
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier Ltd 01.05.2013 Elsevier Pergamon Press Inc
Schlagworte:	Algorithms Applied sciences Black-box Comparative analysis Computation Derivative-free Exact sciences and technology Experimental design Fundamental areas of phenomenology (including applications) Global optimization Integer programming Integers Mathematical analysis Mathematical models Mathematical problems Mathematical programming Mathematics Mixed-integer optimization Multimodal Nonlinear Nonlinearity Operational research and scientific management Operational research. Management science Optimization Optimization algorithms Parametric inference Physics Probability and statistics Radial basis functions Sciences and techniques of general use Searching Solid mechanics Static elasticity (thermoelasticity...) Statistics Structural and continuum mechanics Studies Surrogate model Nonlinear Global optimization Radial basis functions Surrogate model Multimodal Black-box Mixed-integer optimization Derivative-free Black box Adaptive method Optimization Optimal design Function evaluation Nonsmooth analysis Response surface Metamodel Branch and bound method Global optimum Mixed integer programming Search algorithm Radial basis function Genetic algorithm Implicit enumeration method Mixed problem Objective function Reliability
ISSN:	0305-0548, 1873-765X, 0305-0548
Online-Zugang:	Volltext
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