Hitchcock, F. L. (1941). The distribution of a product from several sources to numerous localities. Journal of mathematics and physics, 20(1-4), 224-230.
 Dantzig, G. B., & Thapa, M. N. (2006). Linear programming 2: theory and extensions. Springer Science & Business Media.
 Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
 Zimmermann, H. J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy sets and systems, 1(1), 45-55.
 Chanas, S., Kołodziejczyk, W., & Machaj, A. (1984). A fuzzy approach to the transportation problem. Fuzzy sets and systems, 13(3), 211-221.
 Das, S. K., Mandal, T., & Edalatpanah, S. A. (2017). A mathematical model for solving fully fuzzy linear programming problem with trapezoidal fuzzy numbers. Applied intelligence, 46(3), 509-519.
 Dinagar, D. S., & Palanivel, K. (2009). The transportation problem in fuzzy environment. International journal of algorithms, computing and mathematics, 2(3), 65-71.
 Kaur, A., & Kumar, A. (2011). A new method for solving fuzzy transportation problems using ranking function. Applied mathematical modelling, 35(12), 5652-5661.
 Pandian, P., & Natarajan, G. (2010). A new algorithm for finding a fuzzy optimal solution for fuzzy transportation problems. Applied mathematical sciences, 4(2), 79-90.
 Kundu, P., Kar, S., & Maiti, M. (2013). Some solid transportation models with crisp and rough costs. International journal of mathematical and computational sciences, 7(1), 14-21.
 Kaur, A., & Kumar, A. (2012). A new approach for solving fuzzy transportation problems using generalized trapezoidal fuzzy numbers. Applied soft computing, 12(3), 1201-1213.
 Kundu, P., Kar, S., & Maiti, M. (2014). Multi-objective solid transportation problems with budget constraint in uncertain environment. International journal of systems science, 45(8), 1668-1682.
 Kumar, R., Edalatpanah, S. A., Jha, S., & Singh, R. (2019). A pythagorean fuzzy approach to the transportation problem. Complex & intelligent systems, 5(2), 255-263.
 Liu, P., Yang, L., Wang, L., & Li, S. (2014). A solid transportation problem with type-2 fuzzy variables. Applied soft computing, 24, 543-558.
 Tada, M., & Ishii, H. (1996). An integer fuzzy transportation problem. Computers & mathematics with applications, 31(9), 71-87.
 Liu, S. T., & Kao, C. (2004). Solving fuzzy transportation problems based on extension principle. European journal of operational research, 153(3), 661-674.
 Saad, O. M., & Abass, S. A. (2003). A parametric study on tranportation problem under fuzzy environment. Journal of fuzzy mathematics, 11(1), 115-124.
 A. Charnes, Charnes, A., & Cooper, W. W. (1954). The stepping stone method of explaining linear programming calculations in transportation problems. Management science, 1(1), 49-69.
 Chanas, S., & Kuchta, D. (1996). A concept of the optimal solution of the transportation problem with fuzzy cost coefficients. Fuzzy sets and systems, 82(3), 299-305.
 Maheswari, P. U., & Ganesan, K. (2018, April). Solving fully fuzzy transportation problem using pentagonal fuzzy numbers. Journal of physics: conference series (Vol. 1000, No. 1, p. 012014). IOP Publishing.
 Das, S. K., & Edalatpanah, S. A. (2020). New insight on solving fuzzy linear fractional programming in material aspects. Fuzzy optimization and modelling, 1, 1-7.
 Das, S. K., Mandal, T., & Edalatpanah, S. A. (2017). A new approach for solving fully fuzzy linear fractional programming problems using the multi-objective linear programming. RAIRO-operations research, 51(1), 285-297.
 Das, S. K., Mandal, T., & Behera, D. (2019). A new approach for solving fully fuzzy linear programming problem. International journal of mathematics in operational research, 15(3), 296-309.
 Atanassov K. (1986). Intuitionistic fuzzy sets. Fuzzy sets and systems, 20, 87-96.
 Ebrahimnejad, A., & Verdegay, J. L. (2018). A new approach for solving fully intuitionistic fuzzy transportation problems. Fuzzy optimization and decision making, 17(4), 447-474.
 Nagoorgani, A., & Abbas, S. (2013). A new method for solving intuitionistic fuzzy transportation problem. Applied mathematical science, 7(28), 1357–1365.
 Singh, S. K., & Yadav, S. P. (2016). A new approach for solving intuitionistic fuzzy transportation problem of type-2. Annals of operations research, 243(1-2), 349-363.
 Singh, S. K., & Yadav, S. P. (2015). Efficient approach for solving type-1 intuitionistic fuzzy transportation problem. International journal of system assurance engineering and management, 6(3), 259-267.
 Singh, S. K., & Yadav, S. P. (2016). Intuitionistic fuzzy transportation problem with various kinds of uncertainties in parameters and variables. International journal of system assurance engineering and management, 7(3), 262-272.
 Hussain, R. J., & Kumar, P. S. (2012). Algorithmic approach for solving intuitionistic fuzzy transportation problem. Applied mathematical sciences, 6(80), 3981-3989.
 Aggarwal, S., & Gupta, C. (2017). Sensitivity analysis of intuitionistic fuzzy solid transportation problem. International journal of fuzzy systems, 19(6), 1904-1915.
 Singh, S. K., & Yadav, S. P. (2016). A novel approach for solving fully intuitionistic fuzzy transportation problem. International journal of operational research, 26(4), 460-472.
 Mahmoodirad, A., Allahviranloo, T., & Niroomand, S. (2019). A new effective solution method for fully intuitionistic fuzzy transportation problem. Soft computing, 23(12), 4521-4530.
 Das, S. K., Edalatpanah, S. A., & Mandal, T. (2018). A proposed model for solving fuzzy linear fractional programming problem: numerical point of view. Journal of computational science, 25, 367-375.
 Das, S. K. (2017). Modified method for solving fully fuzzy linear programming problem with triangular fuzzy numbers. International journal of research in industrial engineering, 6(4), 293-311.
 Smarandache, F. (1998). A unifying field in logics: Neutrosophic logic, Neutrosophy, Neutrosophic set, Neutrosophic probability (fifth eition). AmericanResearchPress, Rchoboth.
 Wang, H., Smarandache, F., Zhang, Y. Q., & Sunderraman, R. (2010). Single valued Neutrosophic sets. Multispace and multistructure, 4, 410–413.
 Ye, J. (2018). Neutrosophic number linear programming method and its application under Neutrosophic number environments. Soft computing, 22(14), 4639-4646.
 Roy, R., & Das, P. (2015). A Multi-objective production planning problem based on Neutrosophiclinear programming approach. Infinite Study.
Abdel-Basset, M., Gunasekaran, M., Mohamed, M., & Smarandache, F. (2019). A novel method for solving the fully Neutrosophic linear programming problems. Neural computing and applications, 31(5), 1595-1605.
 Edalatpanah, S. A. (2020). A direct model for triangular Neutrosophic linear programming. International journal of neutrosophic science, 1(1), 19-28.
 Maiti, I., Mandal, T., & Pramanik, S. (2019). Neutrosophic goal programming strategy for multi-level multi-objective linear programming problem. Journal of ambient intelligence and humanized computing, 1-12.
 Edalatpanah, S. A. (2020). Data envelopment analysis based on triangular Neutrosophic numbers. CAAI transactions on intelligence technology. Retrieved from
 Mohamed, M., Abdel-Basset, M., Zaied, A. N. H., & Smarandache, F. (2017). Neutrosophic integer programming problem. Infinite Study.
 Banerjee, D., & Pramanik, S. (2018). Single-objective linear goal programming problem with Neutrosophic numbers. Infinite Study.
 Das, S. K., & Dash, J. K. (2020). Modified solution for Neutrosophic linear programming problems with mixed constraints. International journal of research in industrial engineering, 9(1), 13-24.
 Das, S. K., & Chakraborty, A. (2020). A new approach to evaluate linear programming problem in pentagonal Neutrosophic environment. Complex & intelligent systems, 1-10.
 Chakraborty, A., Mondal, S. P., Alam, S., Ahmadian, A., Senu, N., De, D., & Salahshour, S. (2019). The pentagonal fuzzy number: its different representations, properties, ranking, defuzzification and application in game problems. Symmetry, 11(2), 248.
 Chakraborty, A., Broumi, S., & Singh, P. K. (2019). Some properties of pentagonal Neutrosophic numbers and its applications in transportation problem environment. Neutrosophic sets and systems, 28(1), 16.
 Korukoğlu, S., & Ballı, S. (2011). An improved vogel's approximatio method for the transportation problem. Mathematical and computational applications, 16(2), 370-381.
 Bharati, S. K. (2019). Trapezoidal intuitionistic fuzzy fractional transportation problem. Soft computing for problem solving (pp. 833-842). Springer, Singapore.
 Ahmad, F., & Adhami, A. Y. (2019). Neutrosophic programming approach to multiobjective nonlinear transportation problem with fuzzy parameters. International journal of management science and engineering management, 14(3), 218-229.
 Srinivasan, R., Karthikeyan, N., Renganathan, K., & Vijayan, D. V. (In press). Method for solving fully fuzzy transportation problem to transform the materials. Materials today: proceedings.
 Maiti, I., Mandal, T., Pramanik, S., Das, S.K. (2020). Solving multi-objective linear fractional programming problem based on Stanojevic’s normalization technique under fuzzy environment. International journal of operation research
. DOI: 10.1504/IJOR.2020.10028794