Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem

Halim, A.H. and Ismail, I. (2019) Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem. Archives of Computational Methods in Engineering, 26 (2). pp. 367-380. ISSN 11343060

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The Travelling Salesman Problem (TSP) is an NP-hard problem with high number of possible solutions. The complexity increases with the factorial of n nodes in each specific problem. Meta-heuristic algorithms are an optimization algorithm that able to solve TSP problem towards a satisfactory solution. To date, there are many meta-heuristic algorithms introduced in literatures which consist of different philosophies of intensification and diversification. This paper focuses on 6 heuristic algorithms: Nearest Neighbor, Genetic Algorithm, Simulated Annealing, Tabu Search, Ant Colony Optimization and Tree Physiology Optimization. The study in this paper includes comparison of computation, accuracy and convergence. © 2017, CIMNE, Barcelona, Spain.

Item Type: Article
Additional Information: cited By 76
Uncontrolled Keywords: Ant colony optimization; Combinatorial optimization; Computational complexity; Genetic algorithms; Nearest neighbor search; Philosophical aspects; Problem solving; Simulated annealing; Tabu search; Traveling salesman problem; Trees (mathematics), Intensification and diversifications; Meta heuristic algorithm; Nearest neighbors; Optimization algorithms; Satisfactory solutions; Specific problems; Travelling salesman problem; Travelling salesman problem (TSP), Heuristic algorithms
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:26
Last Modified: 10 Nov 2023 03:26
URI: https://khub.utp.edu.my/scholars/id/eprint/11637

Actions (login required)

View Item
View Item