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Are Quasi-Monte Carlo algorithms efficient for two-stage stochastic programs?
Computational optimization and applications, 2013Quasi-Monte Carlo algorithms are studied for designing discrete approximations of two-stage linear stochastic programs with random right-hand side and continuous probability distribution.
H. Heitsch, H. Leövey, W. Römisch
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Exponential convergence of two-stage stochastic programming
IFAC Proceedings Volumes, 1999Abstract This paper considers a procedure of two-stage stochastic programming in which the performance function to be optimized is replaced by its empirical mean. This procedure converts a stochastic optimization problem into a deterministic one for which many methods are available.
Liyi Dai, Chun-Hung Chen, John Birge
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A deep reinforcement learning framework for solving two-stage stochastic programs
Optimization Letters, 2023Dogacan Yilmaz, I. E. Büyüktahtakin
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Two-Stage Stochastic Programming Problems
1995In this chapter we consider stochastic programming problems where decisions are made in two stages and the observation of a (vector valued) random variable takes place in between. Such problems are called two-stage stochastic programming problems or stochastic programming with recourse.
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A decomposition method for distributionally-robust two-stage stochastic mixed-integer conic programs
Mathematical programming, 2019We develop a decomposition algorithm for distributionally-robust two-stage stochastic mixed-integer convex conic programs, and its important special case of distributionally-robust two-stage stochastic mixed-integer second order conic programs.
Fengqiao Luo, Sanjay Mehrotra
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Deviation Measures in Linear Two-Stage Stochastic Programming
Mathematical Methods of Operations Research, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Risk-Averse Two-Stage Stochastic Program with Distributional Ambiguity
Operations Research, 2018In this paper, we develop a risk-averse two-stage stochastic program (RTSP) that explicitly incorporates the distributional ambiguity covering both discrete and continuous distributions. We formulate RTSP from the perspective of distributional robustness by hedging against the worst-case distribution within an ambiguity set and considering the ...
Ruiwei Jiang, Yongpei Guan
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Two-Stage Stochastic Programming Models and Algorithms
2017This chapter discusses the technical and management solution approaches for solving UC problems under uncertainty. There are many recent programs and studies targeted to uncertainty resistance, such as demand response program, energy storage, real-time rescheduling, contingency management, risk measure and control.
Yuping Huang +2 more
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An accelerated L-shaped method for solving two-stage stochastic programs in disaster management
Annals of Operations Research, 2020E. Grass, Kathrin Fischer, Antonia Rams
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Risk Aversion in Two-Stage Stochastic Integer Programming
2010Some recent developments in the area of risk aversion in stochastic integer programming are surveyed. After a discussion of modeling guidelines and resulting mean–risk stochastic integer programs emphasis is placed on structural properties of these optimization problems and on algorithms for their solution. Bibliographical notes conclude the Chapter.
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