How to cite this paper
Thenepalle, J & Singamsetty, P. (2019). An open close multiple travelling salesman problem with single depot.Decision Science Letters , 8(2), 121-136.
Refrences
Ali, A. I., & Kennington, J. L. (1986). The asymmetric M-travelling salesmen problem: A duality based branch-and-bound algorithm. Discrete Applied Mathematics, 13(2-3), 259-276.
Bektas, T. (2006). The multiple traveling salesman problem: an overview of formulations and solution procedures. Omega, 34(3), 209-219.
Berenguer, X. (1979). A characterization of linear admissible transformations for the m-travelling salesmen problem. European Journal of Operational Research, 3(3), 232-238.
Bhavani, V., & Murthy, M. S. (2006). Truncated M-travelling salesmen problem. Opsearch, 43(2), 152-177.
Bolaños, R., Echeverry, M., & Escobar, J. (2015). A multiobjective non-dominated sorting genetic algorithm (NSGA-II) for the Multiple Traveling Salesman Problem. Decision Science Letters, 4(4), 559-568.
Bolanos, R. (2016). A population-based algorithm for the multi travelling salesman problem. International Journal of Industrial Engineering Computations, 7(2), 245-256.
Carter, A. E., & Ragsdale, C. T. (2006). A new approach to solving the multiple traveling salesperson problem using genetic algorithms. European Journal of Operational Research, 175(1), 246-257.
Changdar, C., Pal, R. K., & Mahapatra, G. S. (2017). A genetic ant colony optimization based algorithm for solid multiple travelling salesmen problem in fuzzy rough environment. Soft Computing, 21(16), 4661-4675.
França, P. M., Gendreau, M., Laporte, G., & Müller, F. M. (1995). The m-traveling salesman problem with minmax objective. Transportation Science, 29(3), 267-275.
Gavish, B., & Srikanth, K. (1986). An optimal solution method for large-scale multiple traveling salesmen problems. Operations Research, 34(5), 698-717.
Kara, I., & Bektas, T. (2006). Integer linear programming formulations of multiple salesman problems and its variations. European Journal of Operational Research, 174(3), 1449-1458.
Király, A., & Abonyi, J. (2010). A novel approach to solve multiple traveling salesmen problem by genetic algorithm. Computational Intelligence in Engineering, 141-151.
Király, A., Christidou, M., Chován, T., Karlopoulos, E., & Abonyi, J. (2016). Minimization of off-grade production in multi-site multi-product plants by solving multiple traveling salesman problem. Journal of Cleaner Production, 111, 253-261.
Larki, H., & Yousefikhoshbakht, M. (2014). Solving the multiple traveling salesman problem by a novel meta-heuristic algorithm. Journal of Optimization in Industrial Engineering, 7(16), 55-63.
Lenstra, J. K., & Kan, A. R. (1979). A characterization of linear admissible transformations for the m-travelling salesmen problem: A result of Berenguer. European Journal of Operational Research, 3(3), 250-252.
Little, J. D., Murty, K. G., Sweeney, D. W., & Karel, C. (1963). An algorithm for the traveling salesman problem. Operations Research, 11(6), 972-989.
Murthy, M. S. (1976). A bulk transportation problem. Opsearch, 13(3–4), 143-155.
Na, B. (2007). Heuristic approaches for no-depot k-traveling salesmen problem with a minmax objective (Doctoral dissertation, Texas A&M University).
Pandit, S. N. (1962). The loading problem. Operations Research, 10(5), 639-646.
Russell, R. A. (1977). An effective heuristic for the m-tour traveling salesman problem with some side conditions. Operations Research, 25(3), 517-524.
Reinhelt, G. (2014). {TSPLIB}: a library of sample instances for the TSP (and related problems) from various sources and of various types. URL: http://comopt. ifi. uniheidelberg. de/software/TSPLIB95.
Sarin, S. C., Sherali, H. D., Judd, J. D., & Tsai, P. F. J. (2014). Multiple asymmetric traveling salesmen problem with and without precedence constraints: Performance comparison of alternative formulations. Computers & Operations Research, 51, 64-89.
Singh, A., & Baghel, A. S. (2009). A new grouping genetic algorithm approach to the multiple traveling salesperson problem. Soft Computing-A Fusion of Foundations, Methodologies and Applications, 13(1), 95-101.
Somhom, S., Modares, A., & Enkawa, T. (1999). Competition-based neural network for the multiple travelling salesmen problem with minmax objective. Computers & Operations Research, 26(4), 395-407.
Soylu, B. (2015). A general variable neighborhood search heuristic for multiple traveling salesmen problem. Computers & Industrial Engineering, 90, 390-401.
Venkatesh, P., & Singh, A. (2015). Two metaheuristic approaches for the multiple traveling salesperson problem. Applied Soft Computing, 26, 74-89.
Wacholder, E., Han, J., & Mann, R. C. (1989). A neural network algorithm for the multiple traveling salesmen problem. Biological Cybernetics, 61(1), 11-19.
Wang, P., Sanin, C., & Szczerbicki, E. (2015). Evolutionary algorithm and decisional DNA for multiple travelling salesman problem. Neurocomputing, 150, 50-57.
Yousefikhoshbakht, M., Didehvar, F., & Rahmati, F. (2013). Modification of the ant colony optimization for solving the multiple traveling salesman problem. Romanian Journal of Information Science and Technology, 16(1), 65-80.
Yuan, S., Skinner, B., Huang, S., & Liu, D. (2013). A new crossover approach for solving the multiple travelling salesmen problem using genetic algorithms. European Journal of Operational Research, 228(1), 72-82.
Bektas, T. (2006). The multiple traveling salesman problem: an overview of formulations and solution procedures. Omega, 34(3), 209-219.
Berenguer, X. (1979). A characterization of linear admissible transformations for the m-travelling salesmen problem. European Journal of Operational Research, 3(3), 232-238.
Bhavani, V., & Murthy, M. S. (2006). Truncated M-travelling salesmen problem. Opsearch, 43(2), 152-177.
Bolaños, R., Echeverry, M., & Escobar, J. (2015). A multiobjective non-dominated sorting genetic algorithm (NSGA-II) for the Multiple Traveling Salesman Problem. Decision Science Letters, 4(4), 559-568.
Bolanos, R. (2016). A population-based algorithm for the multi travelling salesman problem. International Journal of Industrial Engineering Computations, 7(2), 245-256.
Carter, A. E., & Ragsdale, C. T. (2006). A new approach to solving the multiple traveling salesperson problem using genetic algorithms. European Journal of Operational Research, 175(1), 246-257.
Changdar, C., Pal, R. K., & Mahapatra, G. S. (2017). A genetic ant colony optimization based algorithm for solid multiple travelling salesmen problem in fuzzy rough environment. Soft Computing, 21(16), 4661-4675.
França, P. M., Gendreau, M., Laporte, G., & Müller, F. M. (1995). The m-traveling salesman problem with minmax objective. Transportation Science, 29(3), 267-275.
Gavish, B., & Srikanth, K. (1986). An optimal solution method for large-scale multiple traveling salesmen problems. Operations Research, 34(5), 698-717.
Kara, I., & Bektas, T. (2006). Integer linear programming formulations of multiple salesman problems and its variations. European Journal of Operational Research, 174(3), 1449-1458.
Király, A., & Abonyi, J. (2010). A novel approach to solve multiple traveling salesmen problem by genetic algorithm. Computational Intelligence in Engineering, 141-151.
Király, A., Christidou, M., Chován, T., Karlopoulos, E., & Abonyi, J. (2016). Minimization of off-grade production in multi-site multi-product plants by solving multiple traveling salesman problem. Journal of Cleaner Production, 111, 253-261.
Larki, H., & Yousefikhoshbakht, M. (2014). Solving the multiple traveling salesman problem by a novel meta-heuristic algorithm. Journal of Optimization in Industrial Engineering, 7(16), 55-63.
Lenstra, J. K., & Kan, A. R. (1979). A characterization of linear admissible transformations for the m-travelling salesmen problem: A result of Berenguer. European Journal of Operational Research, 3(3), 250-252.
Little, J. D., Murty, K. G., Sweeney, D. W., & Karel, C. (1963). An algorithm for the traveling salesman problem. Operations Research, 11(6), 972-989.
Murthy, M. S. (1976). A bulk transportation problem. Opsearch, 13(3–4), 143-155.
Na, B. (2007). Heuristic approaches for no-depot k-traveling salesmen problem with a minmax objective (Doctoral dissertation, Texas A&M University).
Pandit, S. N. (1962). The loading problem. Operations Research, 10(5), 639-646.
Russell, R. A. (1977). An effective heuristic for the m-tour traveling salesman problem with some side conditions. Operations Research, 25(3), 517-524.
Reinhelt, G. (2014). {TSPLIB}: a library of sample instances for the TSP (and related problems) from various sources and of various types. URL: http://comopt. ifi. uniheidelberg. de/software/TSPLIB95.
Sarin, S. C., Sherali, H. D., Judd, J. D., & Tsai, P. F. J. (2014). Multiple asymmetric traveling salesmen problem with and without precedence constraints: Performance comparison of alternative formulations. Computers & Operations Research, 51, 64-89.
Singh, A., & Baghel, A. S. (2009). A new grouping genetic algorithm approach to the multiple traveling salesperson problem. Soft Computing-A Fusion of Foundations, Methodologies and Applications, 13(1), 95-101.
Somhom, S., Modares, A., & Enkawa, T. (1999). Competition-based neural network for the multiple travelling salesmen problem with minmax objective. Computers & Operations Research, 26(4), 395-407.
Soylu, B. (2015). A general variable neighborhood search heuristic for multiple traveling salesmen problem. Computers & Industrial Engineering, 90, 390-401.
Venkatesh, P., & Singh, A. (2015). Two metaheuristic approaches for the multiple traveling salesperson problem. Applied Soft Computing, 26, 74-89.
Wacholder, E., Han, J., & Mann, R. C. (1989). A neural network algorithm for the multiple traveling salesmen problem. Biological Cybernetics, 61(1), 11-19.
Wang, P., Sanin, C., & Szczerbicki, E. (2015). Evolutionary algorithm and decisional DNA for multiple travelling salesman problem. Neurocomputing, 150, 50-57.
Yousefikhoshbakht, M., Didehvar, F., & Rahmati, F. (2013). Modification of the ant colony optimization for solving the multiple traveling salesman problem. Romanian Journal of Information Science and Technology, 16(1), 65-80.
Yuan, S., Skinner, B., Huang, S., & Liu, D. (2013). A new crossover approach for solving the multiple travelling salesmen problem using genetic algorithms. European Journal of Operational Research, 228(1), 72-82.