Advances Linear Stochastic Programming by Rasekh Lila (8 results)
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Taschenbuch. Condition: Neu. Advances in Linear Stochastic Programming | The Two-Level Decomposition Principle Via Dual Central Pricing | Lila Rasekh | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2009 | VDM Verlag Dr. Müller | EAN 9783639218800 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr…. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.
- Softcover
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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rasekh LilaLila Rasekh holds a Ph. D. degree in Management Science from HEC- Montreal and McGill University in Canada. She currently works in the Decision Science team of Revenu…e Management at Walt Disney World. Her work focuses on.
- Softcover
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 programmi…ng 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 of problems. In addition to extensive discussion on methods for solving multi-stage stochastic program, this book addresses two important production planning challenges namely, stochastic capacity planning; and stochastic in-house production and outsourcing planning. Problems are formulated as large-scale, Multi-stage Stochastic programs and solved implementing an innovative two-level, interior-point decomposition algorithm based on ACCPM.
