Design of Heuristic Algorithms for Hard Optimization: With Python Codes for the Travelling Salesman Problem

This open-access book provides a step-by-step guide to designing heuristic algorithms for difficult optimization problems, using the travelling salesman problem as an example. It deconstructs metaheuristics into key concepts and presents them in a simplified form, with concrete applications of the travelling salesman problem. Two chapters reviewing combinatorial optimization and complexity theory make the book self-contained for readers with a limited background.

Format: Hardback
Length: 287 pages
Publication date: 13 October 2022
Publisher: Springer International Publishing AG

This comprehensive open-access book takes readers on a journey to design heuristic algorithms for challenging optimization problems. Serving as a guiding thread, the classic problem of the traveling salesman is utilized to illustrate various techniques discussed. This problem's inherent intuitiveness and visually representable solutions make it an ideal introduction to the subject. The book is adorned with numerous illustrations that facilitate a quick understanding of the concepts.

The book approaches the primary metaheuristics from a fresh perspective, breaking them down into distinct chapters: construction, improvement, decomposition, randomization, and learning methods. Each metaheuristic is then presented in a simplified form, combining these key concepts. This approach avoids portraying metaheuristics as a non-formal discipline, akin to cloud sculpture. Furthermore, it offers practical applications of the traveling salesman problem, showcasing how to design new heuristics and eliminate ambiguities within a general framework in just a few lines of code.

To ensure self-sufficiency, the book includes two chapters reviewing the fundamentals of combinatorial optimization and complexity theory. This makes it accessible to readers with limited backgrounds in the field, allowing them to fully engage with the content.

In summary, this book is a valuable resource for anyone seeking to develop effective heuristic algorithms for optimization challenges. Its comprehensive coverage, clear explanations, and practical examples make it an essential tool for researchers, practitioners, and students alike.

Weight: 623g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031137136
Edition number: 1st ed. 2023