This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: • It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; • It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; • It accounts for the risk averse nature of decision makers; and • It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.
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This book deals with decision making in environments of significant data uncertainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness approach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making. Beyond theoretical results, the book provides many suggestions and useful advice to the practitioner of the robustness approach. Emphasis is placed upon the assessment of the decision environment for applicability of the approach, structuring of data uncertainty and the scenario generation process, choice of appropriate robustness criteria, and formulation and solution of robust decision problems. The book will be of interest to researchers, practitioners and graduate students working in the fields of operations research, management science, industrial and systems engineering, computer science, decision analysis and applied mathematics.
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Anbieter: Studibuch, Stuttgart, Deutschland
hardcover. Zustand: Gut. 374 Seiten; 9780792342915.3 Gewicht in Gramm: 1. Bestandsnummer des Verkäufers 1110006
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Zustand: Good. Good; Hardcover; Covers are still glossy, but with a few handling-marks to the back cover; Unblemished textblock edges; The endpapers and all text pages are clean and unmarked; The binding is excellent with a straight spine; This book will be stored and delivered in a sturdy cardboard box with foam padding; Medium Format (8.5" - 9.75" tall); Light purple covers with title in black lettering; 1996, Springer-Verlag Publishing; 358 pages; "Robust Discrete Optimization and Its Applications (Nonconvex Optimization and Its Applications)," by Panos Kouvelis & Gang Yu. Bestandsnummer des Verkäufers SKU-W17GA02712229
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: - It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; - It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; - It accounts for the risk averse nature of decision makers; and - It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making. 378 pp. Englisch. Bestandsnummer des Verkäufers 9780792342915
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Gebundene Ausgabe. Zustand: Neu. Neu Neuware, Importqualität, auf Lager - This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: - It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; - It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; - It accounts for the risk averse nature of decision makers; and - It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making. Bestandsnummer des Verkäufers INF1000551776
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Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: ¿ It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; ¿ It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; ¿ It accounts for the risk averse nature of decision makers; and ¿ It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of opera tional decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 378 pp. Englisch. Bestandsnummer des Verkäufers 9780792342915
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Zustand: New. This text deals with decision-making in environments of significant data uncertainty, with particular emphasis on operations and production management applications. It provides a comprehensive mathematical programming framework for robust decision making. Series: Nonconvex Optimization and Its Applications. Num Pages: 374 pages, biography. BIC Classification: PBU; PBW; UM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 22. Weight in Grams: 708. . 1996. Hardback. . . . . Bestandsnummer des Verkäufers V9780792342915
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Zustand: gut. 1996. Robust Discrete Optimization and Its Applications (Nonconvex Optimization and Its Applications, 14, Band 14) In englischer Sprache. pages. Bestandsnummer des Verkäufers BN334810
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