Data-driven spatial branch-and-bound algorithms for box-constrained simulation-based optimization

The ability to use complex computer simulations in quantitative analysis and decision-making is highly desired in science and engineering, at the same rate as computation capabilities and first-principle knowledge advance. Due to the complexity of simulation models, direct embedding of equation-base...

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Veröffentlicht in:	Journal of global optimization Jg. 82; H. 1; S. 21 - 50
Hauptverfasser:	Zhai, Jianyuan, Boukouvala, Fani
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.01.2022 Springer Springer Nature B.V
Schlagworte:	Algorithms Complexity Computer Science Computer simulation Computer-generated environments Decision analysis Decision making First principles Mathematical optimization Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Optimization techniques Real Functions Simulation Spatial data Branch-and-bound Simulation-optimization Convex underestimators Global optimization Black-box optimization
ISSN:	0925-5001, 1573-2916
Online-Zugang:	Volltext
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