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Stochastic optimization

Known as: Stochastic optimisation, Stochastic search 
Stochastic optimization (SO) methods are optimization methods that generate and use random variables. For stochastic problems, the random variables… Expand
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Related topics

Related topics

48 relations
AIMMSCMA-ESConstructive cooperative coevolutionCross-entropy method
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Broader (1)

Estimation theory

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
A unified framework for stochastic optimization
  • W. Powell
  • Eur. J. Oper. Res.
  • 2019
    • Corpus ID: 85512222
Abstract Stochastic optimization is an umbrella term that includes over a dozen fragmented communities, using a patchwork of… Expand
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Review
2018
Review
2018
Particle swarm optimization algorithm: an overview
Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm motivated by intelligent collective… Expand
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Highly Cited
2015
Highly Cited
2015
Adam: A Method for Stochastic Optimization
We introduce Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive… Expand
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Highly Cited
2012
Highly Cited
2012
Real-Time Price-Based Demand Response Management for Residential Appliances via Stochastic Optimization and Robust Optimization
This paper evaluates the real-time price-based demand response (DR) management for residential appliances via stochastic… Expand
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Highly Cited
2012
Highly Cited
2012
Distributed delayed stochastic optimization
We analyze the convergence of gradient-based optimization algorithms that base their updates on delayed stochastic gradient… Expand
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Highly Cited
2010
Highly Cited
2010
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in… Expand
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Highly Cited
2009
Highly Cited
2009
Robust Stochastic Approximation Approach to Stochastic Programming
In this paper we consider optimization problems where the objective function is given in a form of the expectation. A basic… Expand
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Highly Cited
2007
Highly Cited
2007
Introduction to Stochastic Search and Optimization. Estimation, Simulation, and Control (Spall, J.C.
This comprehensive book offers 504 main pages divided into 17 chapters. In addition, five very useful and clearly written… Expand
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Highly Cited
2003
Highly Cited
2003
Introduction to stochastic search and optimization - estimation, simulation, and control
  • J. Spall
  • Wiley-Interscience series in discrete mathematics…
  • 2003
    • Corpus ID: 196611020
A unique interdisciplinary foundation for real-world problem solvingStochastic search and optimization techniques are used in a… Expand
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Highly Cited
1991
Highly Cited
1991
Multi-stage stochastic optimization applied to energy planning
This paper presents a methodology for the solution of multistage stochastic optimization problems, based on the approximation of… Expand
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