UID:
almahu_9949864967402882
Format:
XII, 308 p. 87 illus.
,
online resource.
Edition:
1st ed. 2024.
ISBN:
9783031612619
Series Statement:
International Series in Operations Research & Management Science, 361
Content:
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.
Note:
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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783031612602
Additional Edition:
Printed edition: ISBN 9783031612626
Additional Edition:
Printed edition: ISBN 9783031612633
Language:
English
DOI:
10.1007/978-3-031-61261-9
URL:
https://doi.org/10.1007/978-3-031-61261-9
URL:
Volltext
(URL des Erstveröffentlichers)
Bookmarklink
