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TitleDecision Making Under Uncertainty [electronic resource] : Energy and Power / edited by Claude Greengard, Andrzej Ruszczynski
ImprintNew York, NY : Springer New York, 2002
Connect tohttp://dx.doi.org/10.1007/978-1-4684-9256-9
Descript X, 164 p. online resource

SUMMARY

In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research


CONTENT

Stochastic programming models: wait-and-see versus here-and-now -- Optimal stimulation of oil production -- Power management in a hydro-thermal system under uncertainty by Lagrangian relaxation -- Hedging electricity portfolios via stochastic programming -- Opportunities for stochastic and probabilistic modeling in the deregulated electricity industry -- On supply function bidding in electricity markets -- Qualitative implications of uncertainty in economic equilibrium models -- List of workshop participants


Mathematics Operations research Decision making Functions of real variables Mathematical models Statistics Computational intelligence Environmental management Mathematics Mathematical Modeling and Industrial Mathematics Environmental Management Operation Research/Decision Theory Real Functions Statistics for Engineering Physics Computer Science Chemistry and Earth Sciences Computational Intelligence



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