About this product

Product Identifiers

PublisherSpringer International Publishing A&G

ISBN-103031116844

ISBN-139783031116841

eBay Product ID (ePID)6062648976

Product Key Features

Number of PagesXi, 402 Pages

LanguageEnglish

Publication NameIntroduction to Combinatorial Optimization

Publication Year2023

SubjectComputer Science, Operations Research, General, Optimization

TypeTextbook

AuthorDing-Zhu Du, Xiaodong Hu, Panos M. Pardalos, Weili Wu

Subject AreaMathematics, Computers, Business & Economics

SeriesSpringer Optimization and Its Applications Ser.

FormatTrade Paperback

Dimensions

Item Weight22.4 Oz

Item Length9.3 in

Item Width6.1 in

Additional Product Features

Dewey Edition23

Reviews"This book introduces combinatorial optimization with a methodology-oriented organization. It targets undergraduate and graduate students and contains a good mix of theoretical results (with proof) and examples, which helps the reader acquire ideas and concepts. The chapters end with a list of exercises for the students." (Francisco Chicano, Mathematical Reviews, January, 2024) "The book can appropriately be used as a textbook in a graduate course. All the algorithms are clearly explained and presented. It is a very valuable book for successful application of real problems from combinatorial optimization. ... this book is an excellent contribution to the field of combinatorial optimization, and it is highly recommended to the students and researchers in optimization." (Samir Kumar Neogy, zbMATH 1512.90001, 2023), "The book can appropriately be used as a textbook in a graduate course. All the algorithms are clearly explained and presented. It is a very valuable book for successful application of real problems from combinatorial optimization. ... this book is an excellent contribution to the field of combinatorial optimization, and it is highly recommended to the students and researchers in optimization." (Samir Kumar Neogy, zbMATH 1512.90001, 2023)

Series Volume Number196

Number of Volumes1 vol.

IllustratedYes

Dewey Decimal519.64

Table Of Content1. Introduction.-2. Divide-and-Conquer.- 3. Dynamic Programming and Shortest Path.- 4. Greedy Algorithm and Spanning Tree.- 5. Incremental Method and Maximum Network Flow.- 6. Linear Programming.- 7. Primal-Dual Methods and Minimum Cost Flow.- 8. NP-hard Problems and Approximation Algorithms.- 9. Restriction and Steiner Tree.- 10. Greedy Approximation and Submodular Optimization.- 11. Relaxation and Rounding. 12. Nonsubmodular Optimization.- Bibliography.

SynopsisIntroductory courses in combinatorial optimization are popular at the upper undergraduate/graduate levels in computer science, industrial engineering, and business management/OR, owed to its wide applications in these fields. There are several published textbooks that treat this course and the authors have used many of them in their own teaching experiences. This present text fills a gap and is organized with a stress on methodology and relevant content, providing a step-by-step approach for the student to become proficient in solving combinatorial optimization problems. Applications and problems are considered via recent technology developments including wireless communication, cloud computing, social networks, and machine learning, to name several, and the reader is led to the frontiers of combinatorial optimization. Each chapter presents common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, as well as key algorithms, suchas greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in every chapter, strategically placed graphics, and an extensive bibliography are amongst the gems of this textbook., Introductory courses in combinatorial optimization are popular at the upper undergraduate/graduate levels in computer science, industrial engineering, and business management/OR, owed to its wide applications in these fields. There are several published textbooks that treat this course and the authors have used many of them in their own teaching experiences. This present text fills a gap and is organized with a stress on methodology and relevant content, providing a step-by-step approach for the student to become proficient in solving combinatorial optimization problems. Applications and problems are considered via recent technology developments including wireless communication, cloud computing, social networks, and machine learning, to name several, and the reader is led to the frontiers of combinatorial optimization. Each chapter presents common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, as well as key algorithms, such as greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in every chapter, strategically placed graphics, and an extensive bibliography are amongst the gems of this textbook.

LC Classification NumberQA402.5-402.6