A. H. Halim and I. Ismail, "Combinatorial optimization: comparison of heuristicalgorithms in travelling salesman problem," Archives of Computational Methods inEngineering, vol. 26, pp. 367-380, 2019.
 C. K. Joshi, T. Laurent, and X. Bresson, "An Efficient Graph Convolutional NetworkTechnique for the Travelling Salesman Problem," arXiv preprint arXiv:1906.01227,2019.
 S. S. Juneja, P. Saraswat, K. Singh, J. Sharma, R. Majumdar, and S. Chowdhary,"Travelling Salesman Problem Optimization Using Genetic Algorithm," in 2019 AmityInternational Conference on Artificial Intelligence (AICAI), 2019, pp. 264-268.
 K. Chaudhari and A. Thakkar, "Travelling Salesman Problem: An Empirical ComparisonBetween ACO, PSO, ABC, FA and GA," in Emerging Research in Computing,Information, Communication and Applications, ed: Springer, 2019, pp. 397-405.
 A. Hatamlou, "Solving travelling salesman problem using black hole algorithm," SoftComputing, vol. 22, pp. 8167-8175, 2018.
 Y. Saji and M. E. Riffi, "A novel discrete bat algorithm for solving the travellingsalesman problem," Neural Computing and Applications, vol. 27, pp. 1853-1866, 2016.
 R. Gupta, N. Shrivastava, M. Jain, V. Singh, and A. Rani, "Greedy WOA for TravellingSalesman Problem," in International Conference on Advances in Computing and DataSciences, 2018, pp. 321-330.
 E. L. Lawler, J. K. Lenstra, A. H. Rinnooy Kan, and D. B. Shmoys, "The travelingsalesman problem; a guided tour of combinatorial optimization," 1985.
 V. Tongur and E. Ülker, "The analysis of migrating birds optimization algorithm withneighborhood operator on traveling salesman problem," in Intelligent and EvolutionarySystems, ed: Springer, 2016, pp. 227-237.
 TSPLIB. (2019, 02 Sep.). TSP Library Benchmarks. Available: http://elib.zib.de/pub/mptestdata/tsp/tsplib/tsplib.html
 J. MacQueen, "Some methods for classification and analysis of multivariateobservations," in Proceedings of the fifth Berkeley symposium on mathematical statisticsand probability, 1967, pp. 281-297.
 M. Capó, A. Pérez, and J. A. Lozano, "An efficient approximation to the K-meansclustering for massive data," Knowledge-Based Systems, vol. 117, pp. 56-69, 2017.
 P. Arora and S. Varshney, "Analysis of k-means and k-medoids algorithm for big data,"Procedia Computer Science, vol. 78, pp. 507-512, 2016.
 M. KARAKOYUN, A. SAGLAM, N. A. BAYKAN, and A. A. ALTUN, "Non-locallycolor image segmentation for remote sensing images in different color spaces by usingdata-clustering methods," image, vol. 10, p. 11, 2017.
 T. Velmurugan, "Performance based analysis between k-Means and Fuzzy C-Meansclustering algorithms for connection oriented telecommunication data," Applied SoftComputing, vol. 19, pp. 134-146, 2014.
 M. M. Eusuff and K. E. Lansey, "Optimization of water distribution network design usingthe shuffled frog leaping algorithm," Journal of Water Resources planning andmanagement, vol. 129, pp. 210-225, 2003.
 M. Karakoyun and A. Babalik, "Data clustering with shuffled leaping frog algorithm(SFLA) for classification," in International Conference on Intelligent Computing,Electronics Systems and Information Technology (ICESIT 2015), 2015, pp. 25-26.
 V. K. Jonnalagadda and V. K. D. MALLESHAM, "Bidding strategy of generationcompanies in a competitive electricity market using the shuffled frog leaping algorithm,"Turkish Journal of Electrical Engineering & Computer Sciences, vol. 21, pp. 1567-1583,2013.
 M. Eusuff, K. Lansey, and F. Pasha, "Shuffled frog-leaping algorithm: a memetic metaheuristic for discrete optimization," Engineering optimization, vol. 38, pp. 129-154, 2006.
 V. Jarník, "O jistém problému minimálním," Práca Moravské PrírodovedeckéSpolecnosti, vol. 6, pp. 57-63, 1930.
 R. C. Prim, "Shortest connection networks and some generalizations," The Bell SystemTechnical Journal, vol. 36, pp. 1389-1401, 1957.
 E. W. Dijkstra, "A note on two problems in connexion with graphs," Numerischemathematik, vol. 1, pp. 269-271, 1959.