Pure random search with virtual extension of feasible region

DOI10.1007/s10957-022-02097-wzbMath1505.65220OpenAlexW4296184734MaRDI QIDQ2093284

E. A. Tsvetkov, R. A. Krymov

Publication date: 7 November 2022

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-022-02097-w

zbMATH Keywords

stochastic optimisationboundary pointspure random searchsample size estimation

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Derivative-free methods and methods using generalized derivatives (90C56) Stochastic programming (90C15)

Related Items (1)

Improving exploration strategies in large dimensions and rate of convergence of global random search algorithms

Cites Work

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• Stochastic global optimization.
• Minimization by Random Search Techniques
• Introduction to Stochastic Search and Optimization
• Improvement of pure random search in global optimization
• Optimal strategies of the search for an extremum

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