Decision Making Under Uncertainty

Energy and Power
2002
ISBN: 978-0-387-95465-3
Verlag: Springer

Buch, Englisch, 164 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 442 g

Reihe: The IMA Volumes in Mathematics and its Applications

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.

Zielgruppe

Research

Autoren/Hrsg.

Ruszczynski, Andrzej

Greengard, Claude

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
• Mathematik | Informatik Mathematik Stochastik
• Technische Wissenschaften Energietechnik | Elektrotechnik Energietechnik & Elektrotechnik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Entscheidungstheorie, Sozialwahltheorie

Inhaltsverzeichnis

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.