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An Introduction to Robust Combinatorial Optimization: Concepts, Models and Algorithms for Decision Making under Uncertainty - Tapa dura

Goerigk, Marc; Hartisch, Michael

 
9783031612602: An Introduction to Robust Combinatorial Optimization: Concepts, Models and Algorithms for Decision Making under Uncertainty
Tapa dura
ISBN 10: 3031612604 ISBN 13: 9783031612602
Editorial: Springer-Verlag GmbH, 2024

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

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.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer-Verlag GmbH
Año de publicación
2024
Idioma
Inglés
ISBN 10 
3031612604
ISBN 13 
9783031612602
Encuadernación
Tapa dura
Número de páginas
320
Contacto del fabricante
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