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An Introduction to Robust Combinatorial Optimization: Concepts, Models and Algorithms for Decision Making under Uncertainty: 361 (International Series in Operations Research & Management Science) - Tapa dura
Sinopsis
This book offers a self-contained introduction to the world of robust combinatorial optimization. It explores decision-making using the min-max and min-max regret criteria, while also delving into the two-stage and recoverable robust optimization paradigms. It begins by introducing readers to general results for interval, discrete, and budgeted uncertainty sets, and subsequently provides a comprehensive examination of specific combinatorial problems, including the selection, shortest path, spanning tree, assignment, knapsack, and traveling salesperson problems.
The book equips both students and newcomers to the field with a grasp of the fundamental questions and ongoing advancements in robust optimization. Based on the authors’ years of teaching and refining numerous courses, it not only offers essential tools but also highlights the open questions that define this subject area.
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Acerca del autor
Marc Goerigk is a Professor and Chair of Business Decisions and Data Science at the University of Passau, Germany. He has previously held positions at the Universities of Siegen, Lancaster (UK), Kaiserslautern, and Göttingen, where he pursued his studies in mathematics. Marc has a keen interest in optimization under uncertainty.
Michael Hartisch currently serves as a temporary professor of Analytics & Mixed-Integer Optimization at Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany. Prior to this role, he was acting chair of Network and Data Science Management at the University of Siegen, Germany. His academic journey began with studies in mathematics at Friedrich Schiller University Jena, Germany. Michael’s primary focus is on optimization under uncertainty.
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This book offers a self-contained introduction to the world of robust combinatorial optimization. It explores decision-making using the min-max and min-max regret criteria, while also delving into the two-stage and recoverable robust optimization paradigms. It begins by introducing readers to general results for interval, discrete, and budgeted uncertainty sets, and subsequently provides a comprehensive examination of specific combinatorial problems, including the selection, shortest path, spanning tree, assignment, knapsack, and traveling salesperson problems.
The book equips both students and newcomers to the field with a grasp of the fundamental questions and ongoing advancements in robust optimization. Based on the authors' years of teaching and refining numerous courses, it not only offers essential tools but also highlights the open questions that define this subject area.
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An Introduction to Robust Combinatorial Optimization: Concepts, Models and Algorithms for Decision Making under Uncertainty (International Series in Operations Research & Management Science, 361)
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An Introduction to Robust Combinatorial Optimization: Concepts, Models and Algorithms for Decision Making under Uncertainty (International Series in Operations Research & Management Science, 361)
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An Introduction to Robust Combinatorial Optimization
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An Introduction to Robust Combinatorial Optimization
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Springer, Berlin|Springer Nature Switzerland|Springer, 2024
ISBN 10: 3031612604
ISBN 13: 9783031612602
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book offers a self-contained introduction to the world of robust combinatorial optimization. It explores decision-making using the min-max and min-max regret criteria, while also delving into the two-stage and recoverable robust optimization paradig. Nº de ref. del artículo: 1592583186
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An Introduction to Robust Combinatorial Optimization: Concepts, Models and Algorithms for Decision Making under Uncertainty (International Series in Operations Research & Management Science, 361)
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An Introduction to Robust Combinatorial Optimization
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Springer Nature Switzerland, Springer International Publishing Sep 2024, 2024
ISBN 10: 3031612604
ISBN 13: 9783031612602
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers a self-contained introduction to the world of robust combinatorial optimization. It explores decision-making using the min-max and min-max regret criteria, while also delving into the two-stage and recoverable robust optimization paradigms. It begins by introducing readers to general results for interval, discrete, and budgeted uncertainty sets, and subsequently provides a comprehensive examination of specific combinatorial problems, including the selection, shortest path, spanning tree, assignment, knapsack, and traveling salesperson problems.The book equips both students and newcomers to the field with a grasp of the fundamental questions and ongoing advancements in robust optimization. Based on the authors' years of teaching and refining numerous courses, it not only offers essential tools but also highlights the open questions that define this subject area. 320 pp. Englisch. Nº de ref. del artículo: 9783031612602
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An Introduction to Robust Combinatorial Optimization : Concepts, Models and Algorithms for Decision Making under Uncertainty
Publicado por
Springer Nature Switzerland, Springer International Publishing, 2024
ISBN 10: 3031612604
ISBN 13: 9783031612602
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers a self-contained introduction to the world of robust combinatorial optimization. It explores decision-making using the min-max and min-max regret criteria, while also delving into the two-stage and recoverable robust optimization paradigms. It begins by introducing readers to general results for interval, discrete, and budgeted uncertainty sets, and subsequently provides a comprehensive examination of specific combinatorial problems, including the selection, shortest path, spanning tree, assignment, knapsack, and traveling salesperson problems.The book equips both students and newcomers to the field with a grasp of the fundamental questions and ongoing advancements in robust optimization. Based on the authors' years of teaching and refining numerous courses, it not only offers essential tools but also highlights the open questions that define this subject area. Nº de ref. del artículo: 9783031612602
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An Introduction to Robust Combinatorial Optimization
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Springer Nature Switzerland, Springer Nature Switzerland Aug 2024, 2024
ISBN 10: 3031612604
ISBN 13: 9783031612602
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Buch. Condición: Neu. Neuware -This book offers a self-contained introduction to the world of robust combinatorial optimization. It explores decision-making using the min-max and min-max regret criteria, while also delving into the two-stage and recoverable robust optimization paradigms. It begins by introducing readers to general results for interval, discrete, and budgeted uncertainty sets, and subsequently provides a comprehensive examination of specific combinatorial problems, including the selection, shortest path, spanning tree, assignment, knapsack, and traveling salesperson problems.The book equips both students and newcomers to the field with a grasp of the fundamental questions and ongoing advancements in robust optimization. Based on the authors¿ years of teaching and refining numerous courses, it not only offers essential tools but also highlights the open questions that define this subject area.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch. Nº de ref. del artículo: 9783031612602
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An Introduction to Robust Combinatorial Optimization: Concepts, Models and Algorithms for Decision Making Under Uncertainty
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An Introduction to Robust Combinatorial Optimization (Hardcover)
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Springer International Publishing AG, Cham, 2024
ISBN 10: 3031612604
ISBN 13: 9783031612602
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Hardcover. Condición: new. Hardcover. This book offers a self-contained introduction to the world of robust combinatorial optimization. It explores decision-making using the min-max and min-max regret criteria, while also delving into the two-stage and recoverable robust optimization paradigms. It begins by introducing readers to general results for interval, discrete, and budgeted uncertainty sets, and subsequently provides a comprehensive examination of specific combinatorial problems, including the selection, shortest path, spanning tree, assignment, knapsack, and traveling salesperson problems.The book equips both students and newcomers to the field with a grasp of the fundamental questions and ongoing advancements in robust optimization. Based on the authors years of teaching and refining numerous courses, it not only offers essential tools but also highlights the open questions that define this subject area. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783031612602
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