The Probabilistic Minimum Spanning Tree Problem (Classic Reprint)

Dimitris Bertsimas

ISBN 10: 1332276091 / ISBN 13: 9781332276097

Published by Forgotten Books, 2018

About this Item

Print on Demand. This book explores the probabilistic minimum spanning tree problem (PMST), a probabilistic variation of the classic minimum spanning tree problem. Unlike its deterministic counterpart, the PMST considers situations where not all points are deterministically present, but instead have certain probabilities of presence. The author, a respected researcher in the field, delves into the complexity and combinatorial properties of the problem, proving that even a restricted version of the PMST with all weights equal is NP-complete, a surprising result given the simplicity of the MST problem. The book also examines the relationship between the PMST problem and the MST, network design, and re-optimization strategies, providing valuable insights into the problem's nature and potential applications. Through the author's rigorous analysis and clear explanations, this book offers a comprehensive understanding of the PMST problem, its complexities, and its implications in the broader field of combinatorial optimization. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book.

Seller Inventory # 9781332276097_0

Bibliographic Details

• Title: The Probabilistic Minimum Spanning Tree Problem (Classic Reprint)
• Publisher: Forgotten Books
• Publication Date: 2018
• Language: English
• ISBN 10: 1332276091
• ISBN 13: 9781332276097
• Binding: Paperback
• Condition: New
• Book Type: print-on-demand item
• Seller catalogs:
  • Calculus

About this title

Synopsis

This book explores the probabilistic minimum spanning tree problem (PMST), a probabilistic variation of the classic minimum spanning tree problem. Unlike its deterministic counterpart, the PMST considers situations where not all points are deterministically present, but instead have certain probabilities of presence. The author, a respected researcher in the field, delves into the complexity and combinatorial properties of the problem, proving that even a restricted version of the PMST with all weights equal is NP-complete, a surprising result given the simplicity of the MST problem. The book also examines the relationship between the PMST problem and the MST, network design, and re-optimization strategies, providing valuable insights into the problem's nature and potential applications. Through the author's rigorous analysis and clear explanations, this book offers a comprehensive understanding of the PMST problem, its complexities, and its implications in the broader field of combinatorial optimization.