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Cited by 5
Application of the Monte‐Carlo Method to Nonlinear Stochastic Optimization with Linear Constraints

Simulation-Based Modelling of a Stochastic Equilibrium
Leonidas Sakalauskas
https://doi.org/10.1007/978-1-4899-7547-8_3
Book:  Operations Research/Computer Science Interfaces Series (Uncertainty Management in Simulation-Optimization of Complex Systems) Volume 59 (2015), p. 55
International Workshop of "Stochastic Programming for Implementation and Advanced Applications"
Valerijonas Dumskis, Vincent Guigues, Leonidas Sakalauskas
https://doi.org/10.5200/stoprog.2012.04
Conference:  (2012), p. 19
Towards Implementable Nonlinear Stochastic Programming
L. Sakalauskas
https://doi.org/10.1007/3-540-35262-7_15
Book:  Lecture Notes in Economics and Mathematical Systems (Coping with Uncertainty) Volume 581 (2006), p. 257
Distributed Software Development Tools for Distributed Scientific Applications
Vaidas Giedrimas, Leonidas Sakalauskas, Anatoly Petrenko
https://doi.org/10.5772/intechopen.68334
Book:  (2017)
A review of Monte Carlo and quasi‐Monte Carlo sampling techniques
Ying‐Chao Hung
https://doi.org/10.1002/wics.1637
Journal:  WIREs Computational Statistics Volume 16, Issue 1 (2024)


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