Traveling Salesman Problem Optimization with the Attractor-Based Search System
Produktdetaljer
Om bidragsyterne
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).
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.
This book presents a new search paradigm for solving the Traveling Salesman Problem (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.
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.
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
Produktdetaljer
Om bidragsyterne
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).