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The Traveling Salesman Problem: Optimization with the Attractor-Based Search System de Weiqi Li

The Traveling Salesman Problem: Optimization with the Attractor-Based Search System: Synthesis Lectures on Operations Research and Applications

Autor Weiqi Li
en Limba Engleză Hardback – 9 iul 2023
This book presents a new search paradigm for solving the Traveling Salesman Problem (TSP). The intrinsic difficulty of the TSP is associated with the combinatorial explosion of potential solutions in the solution space. The author introduces the idea of using the attractor concept in dynamical systems theory to reduce the search space for exhaustive search for the TSP. Numerous examples are used to describe how to use this new search algorithm to solve the TSP and its variants including: multi-objective TSP, dynamic TSP, and probabilistic TSP. This book is intended for readers in the field of optimization research and application.
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Specificații

ISBN-13: 9783031357183
ISBN-10: 3031357183
Pagini: 141
Ilustrații: XIV, 141 p. 66 illus., 8 illus. in color.
Dimensiuni: 168 x 240 mm
Greutate: 0.41 kg
Ediția:1st ed. 2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria Synthesis Lectures on Operations Research and Applications

Locul publicării:Cham, Switzerland

Cuprins

Introduction.- The Traveling Salesman Problem (TSP).- The Nature of Heuristic Local Search.- he Attractor-Based Search System.- Solving Multi-objective TSP.- Solving Dynamic TSP.- Solving Probabilistic TSP.- Conclusion.

Notă biografică

Weiqi Li, PhD, is an Associate Professor at the University of Michigan – Flint and an affiliated faculty in the Michigan Institute for Data Science at the University of Michigan. His research interests include combinatorial optimization, heuristics, supply chain management, and artificial intelligence. Specifically, Dr. Li’s research focuses on new search methods to solve the traveling salesman problem (TSP).

Textul de pe ultima copertă

This book presents a new search paradigm for solving the Traveling Salesman Problem (TSP). The intrinsic difficulty of the TSP is associated with the combinatorial explosion of potential solutions in the solution space. The author introduces the idea of using the attractor concept in dynamical systems theory to reduce the search space for exhaustive search for the TSP. Numerous examples are used to describe how to use this new search algorithm to solve the TSP and its variants including: multi-objective TSP, dynamic TSP, and probabilistic TSP. This book is intended for readers in the field of optimization research and application.

In addition, this book:
  • Provides a complete understanding of the attractor concept in heuristic local searches
  • Presents a new search paradigm for solving a NP-complete combinatorial problem
  • Introduces the use of the attractor concept in dynamical systems theory to reduce the search space for TSP

Caracteristici

Provides a complete understanding of the attractor concept in heuristic local searches Presents a new search paradigm for solving a NP-complete combinatorial problem Introduces the use of the attractor concept in dynamical systems theory to reduce the search space for TSP