Cantitate/Preț
Produs

An Introduction to Robust Combinatorial Optimization: Concepts, Models and Algorithms for Decision Making under Uncertainty: International Series in Operations Research & Management Science, cartea 361

Autor Marc Goerigk, Michael Hartisch
en Limba Engleză Hardback – 15 sep 2024
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.
Citește tot Restrânge

Din seria International Series in Operations Research & Management Science

Preț: 72333 lei

Preț vechi: 88212 lei
-18% Nou

Puncte Express: 1085

Preț estimativ în valută:
13858 14590$ 11439£

Carte disponibilă

Livrare economică 01-15 ianuarie 25

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783031612602
ISBN-10: 3031612604
Ilustrații: X, 390 p. 54 illus. in color.
Dimensiuni: 155 x 235 mm
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria International Series in Operations Research & Management Science

Locul publicării:Cham, Switzerland

Cuprins

1. Introduction.- 2. Basic Concepts.- 3. Robust Problems.- 4. General Reformulation Results.- 5. General Solution Methods.- 6. Robust  election Problems.- 7. Robust Shortest Path Problems.- 8. Robust Spanning Tree Problems.- 9. Other Combinatorial Problems.- 10. Other Models for Robust Optimization.- 11. Open Problems.

Notă biografică

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.

Textul de pe ultima copertă

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.

Caracteristici

Provides a comprehensive overview of basic results and state-of-the-art knowledge on robust combinatorial optimization Contains numerous examples and exercises with solutions Includes a collection of open problems in the field