Advances in Linear Stochastic Programming
Lila Rasekh
Broschiertes Buch

Advances in Linear Stochastic Programming

The Two-Level Decomposition Principle Via Dual Central Pricing

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Multi-stage Stochastic Programming (MSP) has many practical applications for solving problems whose current resolution must be made while taking into account future uncertainty. A variety of methods exist for solving stochastic programming problems, among them are: direct methods such as simplex and interior point methods, and decomposition methods such as ACCPM (Analytic Center Cutting Plane Method), Dantzig-Wolfe and Benders decompositions, and L-shaped method. Moreover, approximation methods such as Monte Carlo simulation, as well as combinatorial heuristics are employed to solve this class...