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Decision Making Under Uncertainty Energy and Power [Paperback]

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  • Category: Books (Mathematics)
  • ISBN-10:  1441930140
  • ISBN-10:  1441930140
  • ISBN-13:  9781441930149
  • ISBN-13:  9781441930149
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  164
  • Pages:  164
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Mar-2010
  • Pub Date:  01-Mar-2010
  • SKU:  1441930140-11-SPRI
  • SKU:  1441930140-11-SPRI
  • Item ID: 100753362
  • List Price: $109.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Jul 08 to Jul 10
  • Notes: Brand New Book. Order Now.
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.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 rlóË
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