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Monte Carlo sampling-based methods for stochastic optimization · Study

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ArticleMonte Carlo sampling-based methods for stochastic optimization

Tito Homem‐de‐Mello2014

Article2014

Monte Carlo sampling-based methods for stochastic optimization

Tito Homem‐de‐Mello · Güzi̇n Bayraksan

286 citations·0/0 files stored·Surveys in Operations Research and Management Science

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Simulation Techniques and Applications Risk and Portfolio Optimization Markov Chains and Monte Carlo Methods

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References

2019Theory of games and economic behavior 1951A Stochastic Approximation Method 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code 1945Theory of Games and Economic Behavior 1946Theory of Games and Economic Behavior 1979Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code 1959Chance-Constrained Programming 1987Large Sample Properties of Simulations Using Latin Hypercube Sampling

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2017Robust sample average approximation 2020Sustainable cold supply chain management under demand uncertainty and carbon tax regulation 2016Wait-and-judge scenario optimization 2019A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice 2022Stochastic optimization models for location and inventory prepositioning of disaster relief supplies 2019

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Year2014

Typearticle

Published2014-01-01

VenueSurveys in Operations Research and Management Science

ISSN-L1876-7354

Languageen

Citations286

Files0 public / 0

ShelfSimulation Techniques and Applications

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doi10.1016/j.sorms.2014.05.001

openalex_workW1983221302

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Risk and complexity in scenario optimization

2022Optimization-Based Scenario Reduction for Data-Driven Two-Stage Stochastic Optimization

2016An enhanced sample average approximation method for stochastic optimization