Introduction to Combinatorial Optimization

Combinatorial optimization is a popular course at the upper undergraduate/graduate levels in computer science, industrial engineering, and business management. This textbook provides a step-by-step approach for the student to become proficient in solving combinatorial optimization problems, with applications and problems considered via recent technology developments. It includes common problems, key algorithms, exercises, graphics, and an extensive bibliography.

Format: Hardback
Length: 402 pages
Publication date: 03 October 2022
Publisher: Springer International Publishing AG

Combinatorial optimization is a highly sought-after field of study at the upper undergraduate and graduate levels in computer science, industrial engineering, and business management. Its broad applications in these domains have contributed to its popularity. Numerous published textbooks have been utilized in teaching this course, and the authors have drawn from these resources in their own teaching experiences. This present text aims to bridge a gap and provides a comprehensive and methodical approach to mastering combinatorial optimization problems. It incorporates recent technological advancements, such as wireless communication, cloud computing, social networks, and machine learning, to explore applications and problems in this field. The reader is guided to the forefront of combinatorial optimization, with each chapter presenting common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, and key algorithms, including greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in each chapter, strategically placed graphics, and an extensive bibliography further enrich the textbook's value.

Combinatorial optimization is a field of study that has gained significant popularity at the upper undergraduate and graduate levels in computer science, industrial engineering, and business management. Its broad applications in these domains have contributed to its allure. Numerous published textbooks have been utilized in teaching this course, and the authors have drawn from these resources in their own teaching experiences. This present text aims to bridge a gap and provides a comprehensive and methodical approach to mastering combinatorial optimization problems. It incorporates recent technological advancements, such as wireless communication, cloud computing, social networks, and machine learning, to explore applications and problems in this field. The reader is guided to the forefront of combinatorial optimization, with each chapter presenting common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, and key algorithms, including greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in each chapter, strategically placed graphics, and an extensive bibliography further enrich the textbook's value.

Combinatorial optimization is a field of study that has gained significant popularity at the upper undergraduate and graduate levels in computer science, industrial engineering, and business management. Its broad applications in these domains have contributed to its allure. Numerous published textbooks have been utilized in teaching this course, and the authors have drawn from these resources in their own teaching experiences. This present text aims to bridge a gap and provides a comprehensive and methodical approach to mastering combinatorial optimization problems. It incorporates recent technological advancements, such as wireless communication, cloud computing, social networks, and machine learning, to explore applications and problems in this field. The reader is guided to the forefront of combinatorial optimization, with each chapter presenting common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, and key algorithms, including greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in each chapter, strategically placed graphics, and an extensive bibliography further enrich the textbook's value.

Weight: 772g
Dimension: 160 x 243 x 30 (mm)
ISBN-13: 9783031105944
Edition number: 1st ed. 2022