Applications of Stochastic Programming
Stein W. Wallace, William T. Ziemba
SIAM, Jun 1, 2005 - Mathematics - 709 pages
This is the first book devoted to the full scale of applications of stochastic programming, and to provide access to publicly available algorithmic systems. The 32 contributed papers are written by leading stochastic programming specialists and reflect the recent advanced research on algorithms and applications. The book consists of two parts: the first presents papers describing publicly available stochastic programming systems that are currently operational. All the codes have been extensively tested and developed and will appeal to researchers and developers wanting to make models without extensive programming and other implementation costs. The second part of the book is a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity. It contains the most complete collection of real applications using stochastic programming available in the literature.
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algebraic modeling languages algorithm allocation application approach approximation asset bonds capacity components computational constraints cost CPLEX CVaR decision variables decomposition defined demand denote deterministic deterministic equivalent distribution dynamic EKKStoch estimates eutrophication event tree example expected Figure forecast formulation hedge funds horizon implemented index funds input integrated inventory investment Lake Balaton linear programming losses Math maximize method minimize modeling languages multistage stochastic node objective function Oper optimization model optimization problem option param parameters period portfolio probability random variables recourse region risk management sample scenario tree simulation SLP-IOR SMPS solution solver solving specific stage stoch stochastic linear programs stochastic optimization stochastic process stochastic programming stochastic programming model strategy structure subproblem supply chain Table two-stage uncertainty utility vector yacht ZIEMBA