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Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem

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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.

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Authors and Affiliations

  1. Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, 31750, Tronoh, Perak, Malaysia

    A. Hanif Halim & I. Ismail

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  1. A. Hanif Halim
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  2. I. Ismail
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Correspondence to A. Hanif Halim.

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Halim, A.H., Ismail, I. Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem. Arch Computat Methods Eng 26, 367–380 (2019). https://doi.org/10.1007/s11831-017-9247-y

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  • DOI: https://doi.org/10.1007/s11831-017-9247-y

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