Algorithms for Worst-Case Design and Applications to Risk Management

Berc Rustem, Melendres Howe

Edité par Princeton University Press
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Titre : Algorithms for Worst-Case Design and ...
Éditeur : Princeton University Press
Etat du livre : Good

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Rustem, Berç; Howe, Melendres
Edité par Princeton University Press (2002)
ISBN 10 : 0691091544 ISBN 13 : 9780691091549
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Description du livre Princeton University Press, 2002. Hardcover. État : Used: Very Good. This is an ex-library book that is in new condition. Has no stamps, only two stickers, pages are clean and it was never read *** Hard-Bound with dust-cover *** Princeton University Press. N° de réf. du libraire A-PUP-14681

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Rustem, Berç, Howe, Melendres
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Description du livre Princeton University Press, 2017. Hardcover. État : New. This item is printed on demand. N° de réf. du libraire P110691091544

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Berç Rustem, Melendres Howe
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Description du livre Princeton University Press, 2002. Hardcover. État : New. N° de réf. du libraire DADAX0691091544

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Berc Rustem, Melendres Howe
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Description du livre Princeton University Press, United States, 2002. Hardback. État : New. New.. Language: English . Brand New Book. Recognizing that robust decision making is vital in risk management, this book provides concepts and algorithms for computing the best decision in view of the worst-case scenario. The main tool used is minimax, which ensures robust policies with guaranteed optimal performance that will improve further if the worst case is not realized. The applications considered are drawn from finance, but the design and algorithms presented are equally applicable to problems of economic policy, engineering design, and other areas of decision making. Critically, worst-case design addresses not only Armageddon-type uncertainty. Indeed, the determination of the worst case becomes nontrivial when faced with numerous--possibly infinite--and reasonably likely rival scenarios. Optimality does not depend on any single scenario but on all the scenarios under consideration. Worst-case optimal decisions provide guaranteed optimal performance for systems operating within the specified scenario range indicating the uncertainty. The noninferiority of minimax solutions--which also offer the possibility of multiple maxima--ensures this optimality.Worst-case design is not intended to necessarily replace expected value optimization when the underlying uncertainty is stochastic. However, wise decision making requires the justification of policies based on expected value optimization in view of the worst-case scenario. Conversely, the cost of the assured performance provided by robust worst-case decision making needs to be evaluated relative to optimal expected values. Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable to practitioners in risk management. N° de réf. du libraire AAH9780691091549

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Berc Rustem, Melendres Howe
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ISBN 10 : 0691091544 ISBN 13 : 9780691091549
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Description du livre Princeton University Press, United States, 2002. Hardback. État : New. New.. Language: English . Brand New Book. Recognizing that robust decision making is vital in risk management, this book provides concepts and algorithms for computing the best decision in view of the worst-case scenario. The main tool used is minimax, which ensures robust policies with guaranteed optimal performance that will improve further if the worst case is not realized. The applications considered are drawn from finance, but the design and algorithms presented are equally applicable to problems of economic policy, engineering design, and other areas of decision making. Critically, worst-case design addresses not only Armageddon-type uncertainty. Indeed, the determination of the worst case becomes nontrivial when faced with numerous--possibly infinite--and reasonably likely rival scenarios. Optimality does not depend on any single scenario but on all the scenarios under consideration. Worst-case optimal decisions provide guaranteed optimal performance for systems operating within the specified scenario range indicating the uncertainty. The noninferiority of minimax solutions--which also offer the possibility of multiple maxima--ensures this optimality. Worst-case design is not intended to necessarily replace expected value optimization when the underlying uncertainty is stochastic. However, wise decision making requires the justification of policies based on expected value optimization in view of the worst-case scenario. Conversely, the cost of the assured performance provided by robust worst-case decision making needs to be evaluated relative to optimal expected values. Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable to practitioners in risk management. N° de réf. du libraire AAH9780691091549

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Berç Rustem; Melendres Howe
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ISBN 10 : 0691091544 ISBN 13 : 9780691091549
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Description du livre Princeton University Press, 2002. Hardcover. État : New. book. N° de réf. du libraire 0691091544

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Description du livre Princeton University Press. Hardback. État : new. BRAND NEW, Algorithms for Worst-Case Design and Applications to Risk Management, Berc Rustem, Melendres Howe, Recognizing that robust decision making is vital in risk management, this book provides concepts and algorithms for computing the best decision in view of the worst-case scenario. The main tool used is minimax, which ensures robust policies with guaranteed optimal performance that will improve further if the worst case is not realized. The applications considered are drawn from finance, but the design and algorithms presented are equally applicable to problems of economic policy, engineering design, and other areas of decision making. Critically, worst-case design addresses not only Armageddon-type uncertainty. Indeed, the determination of the worst case becomes nontrivial when faced with numerous--possibly infinite--and reasonably likely rival scenarios. Optimality does not depend on any single scenario but on all the scenarios under consideration. Worst-case optimal decisions provide guaranteed optimal performance for systems operating within the specified scenario range indicating the uncertainty. The noninferiority of minimax solutions--which also offer the possibility of multiple maxima--ensures this optimality. Worst-case design is not intended to necessarily replace expected value optimization when the underlying uncertainty is stochastic. However, wise decision making requires the justification of policies based on expected value optimization in view of the worst-case scenario. Conversely, the cost of the assured performance provided by robust worst-case decision making needs to be evaluated relative to optimal expected values. Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable to practitioners in risk management. N° de réf. du libraire B9780691091549

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Rustem, Berç; Howe, Melendres
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Description du livre Princeton University Press, 2002. Hardcover. État : New. N° de réf. du libraire INGM9780691091549

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Berc Rustem, Melendres Howe
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Description du livre Princeton University Press, United States, 2002. Hardback. État : New. New.. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. Recognizing that robust decision making is vital in risk management, this book provides concepts and algorithms for computing the best decision in view of the worst-case scenario. The main tool used is minimax, which ensures robust policies with guaranteed optimal performance that will improve further if the worst case is not realized. The applications considered are drawn from finance, but the design and algorithms presented are equally applicable to problems of economic policy, engineering design, and other areas of decision making. Critically, worst-case design addresses not only Armageddon-type uncertainty. Indeed, the determination of the worst case becomes nontrivial when faced with numerous--possibly infinite--and reasonably likely rival scenarios. Optimality does not depend on any single scenario but on all the scenarios under consideration. Worst-case optimal decisions provide guaranteed optimal performance for systems operating within the specified scenario range indicating the uncertainty. The noninferiority of minimax solutions--which also offer the possibility of multiple maxima--ensures this optimality. Worst-case design is not intended to necessarily replace expected value optimization when the underlying uncertainty is stochastic. However, wise decision making requires the justification of policies based on expected value optimization in view of the worst-case scenario. Conversely, the cost of the assured performance provided by robust worst-case decision making needs to be evaluated relative to optimal expected values. Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable to practitioners in risk management. N° de réf. du libraire BTE9780691091549

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Description du livre Princeton Univ Pr, 2002. Hardcover. État : Brand New. 408 pages. 9.50x6.75x1.25 inches. In Stock. N° de réf. du libraire __0691091544

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