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Multistage stochastic programming modeling for farmland irrigation management under uncertainty. [PDF]
Farmland management and irrigation scheduling are vital to a productive agricultural economy. A multistage stochastic programming model is proposed to maximize farmers' annual profit under uncertainty.
Qi Li, Guiping Hu
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Stochastic Constraint Programming
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a ...
Walsh, Toby
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A stochastic approximation algorithm for stochastic semidefinite programming [PDF]
Motivated by applications to multi-antenna wireless networks, we propose a distributed and asynchronous algorithm for stochastic semidefinite programming.
Gaujal, Bruno, Mertikopoulos, Panayotis
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Applications of Stochastic Mixed-Integer Second-Order Cone Optimization
Second-order cone programming problems are a tractable subclass of convex optimization problems that can be solved using polynomial algorithms. In the last decade, stochastic second-order cone programming problems have been studied, and efficient ...
Baha Alzalg, Hadjer Alioui
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A Review of Stochastic Programming Methods for Optimization of Process Systems Under Uncertainty
Uncertainties are widespread in the optimization of process systems, such as uncertainties in process technologies, prices, and customer demands. In this paper, we review the basic concepts and recent advances of a risk-neutral mathematical framework ...
Can Li, Ignacio E. Grossmann
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About a regional development model that takes into account environmental problems with budgeting uncertainty [PDF]
Raw-materials base (hereinafter RMB) is one of the largest industries for financial investments in Russia. There are various mathematical descriptions for the development of regions with resource-based economy.
Novikov Artem
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Output‐feedback stochastic model predictive control of chance‐constrained nonlinear systems
This study covers the output‐feedback model predictive control (MPC) of nonlinear systems subjected to stochastic disturbances and state chance constraints. The stochastic optimal control problem is solved in a stochastic dynamic programming fashion, and
Jingyu Zhang, Toshiyuki Ohtsuka
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Natural gas supply chain under uncertainty condition [PDF]
In today’s competitive world, uncertainty is an integral part of all optimization problems. One of the cases where uncertainty has the greatest impact on optimization issues is SCN design.
Reza Mohammadi
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The purpose of this paper is to apply multistage stochastic programming to the transmission line expansion planning problem, especially when uncertain demand scenarios exist. Since the problem of transmission line expansion planning requires an intensive
Sini Han, Hyeon-Jin Kim, Duehee Lee
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New energy power systems with high-permeability photovoltaic and wind power are high-dimensional dynamic large-scale systems with nonlinear, uncertain and complex operating characteristics.
Xueqian Fu, Xianping Wu, Nian Liu
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