@article{scholars11637,
           title = {Combinatorial Optimization: Comparison of Heuristic Algorithms in Travelling Salesman Problem},
          number = {2},
          volume = {26},
            note = {cited By 76},
             doi = {10.1007/s11831-017-9247-y},
       publisher = {Springer Netherlands},
         journal = {Archives of Computational Methods in Engineering},
           pages = {367--380},
            year = {2019},
            issn = {11343060},
          author = {Halim, A. H. and Ismail, I.},
        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},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034599867&doi=10.1007\%2fs11831-017-9247-y&partnerID=40&md5=09f0f0dd53f74be695248768e2e93740},
        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. {\^A}{\copyright} 2017, CIMNE, Barcelona, Spain.}
}