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Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem
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Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem
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Journal Article
Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem
2019
Overview
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.
Publisher
Springer Nature B.V
