References

[1]               Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.

[2]               Zadeh, L. A. (1973). Outline of a new approach to the analysis of complex systems and  decision processes. IEEE Transactions on systems, Man, and Cybernetics, (1), 28-44.

[3]               Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate   reasoning—I. Information sciences, 8(3), 199-249.

[4]               Atanssov, K. T. (1986). Intuitionistic fuzzy set. Fuzzy Sets and Systems, 20, 87-96.

[5]               Smarandache, F.(1998). Neutrosophy: Neutrosophic Probability, Set, and Logic; American Research Press: Rehoboth, MA, USA.

[6]               Ye, J. (2014). Similarity measures between interval neutrosophic sets and their applications  in multicriteria decision-making. Journal of Intelligent & Fuzzy Systems, 26(1), 165-172.

[7]               Broumi, S., Smarandache, F., Talea, M., & Bakali, A. (2016). An introduction to bipolar  single valued neutrosophic graph theory. In Applied Mechanics and Materials (Vol. 841, pp. 184-191). Trans Tech Publications.

[8]               Ji, P., Wang, J. Q., & Zhang, H. Y. (2018). Frank prioritized Bonferroni mean operator with  single-valued neutrosophic sets and its application in selecting third-party logistics providers.  Neural Computing and Applications, 30(3), 799-823.

[9]                Peng, H. G., Zhang, H. Y., & Wang, J. Q. (2018). Probability multi-valued neutrosophic sets  and its application in multi-criteria group decision-making problems. Neural Computing and  Applications, 30(2), 563-583.

[10]           Wang, J. Q., Zhang, X., & Zhang, H. Y. (2018). Hotel recommendation approach based on the online consumer reviews using interval neutrosophic linguistic numbers. Journal of Intelligent & Fuzzy Systems, 34(1), 381-394.

[11]           Kumar, R., Edalatpanah, S. A., Jha, S., & Singh, R. (2019). A novel approach to solve  gaussian  valued neutrosophic shortest path problems, International Journal of Engineering  and Advanced Technology. 8, 347-353.

[12]           Kumar, R., Edalatpanah, S. A., Jha, S., Broumi, S., Singh, R., & Dey, A. (2019). A Multi   Objective Programming Approach to Solve Integer Valued Neutrosophic Shortest Path   Problems. Neutrosoph Sets Syst, 24, 134-149.

[13]           Edalatpanah, S. A. (2018). Neutrosophic perspective on DEA. Journal of Applied Research  on Industrial Engineering, 5(4), 339-345.

[14]           Edalatpanah, S. A., & Smarandache, F. (2019). Data Envelopment Analysis for Simplified Neutrosophic Sets. Neutrosophic Sets & Systems, 29.215-226.

[15]           Said Broumi, Assia Bakali, Mohamed Talea, Florentin Smarandache, K. P. Krishnan Kishore, Rıdvan Şahin, Shortest Path Problem under Interval Valued Neutrosophic Setting, International Journal of Advanced Trends in Computer Science and Engineering, Volume 8, No.1.1, 2019,pp.216-222.

[16]           S. Broumi, A. Dey, M. Talea, A. Bakali, F. Smarandache, D. Nagarajan, M. Lathamaheswari and Ranjan Kumar(2019), “Shortest Path Problem using Bellman Algorithm under Neutrosophic Environment,” Complex & Intelligent Systems ,pp-1-8, https://doi.org/10.1007/s40747-019-0101-8,

[17]           S. Broumi, M.Talea, A. Bakali, F. Smarandache, D.Nagarajan, M. Lathamaheswari and M.Parimala, Shortest path problem in fuzzy, intuitionistic fuzzy and neutrosophic environment: an overview, Complex & Intelligent Systems ,2019,pp 1-8, https://doi.org/10.1007/s40747-019-0098-z

[18]           S.Broumi,D. Nagarajan, A. Bakali, M. Talea, F. Smarandache, M. Lathamaheswari, The shortest path problem in interval valued trapezoidal and triangular neutrosophic environment, Complex & Intelligent Systems , 2019,pp 1-12, https://doi.org/10.1007/s40747-019-0092-5

[19]           Said Broumi, Mohamed Talea, Assia Bakali, Prem Kumar Singh, Florentin Smarandache: Energy and Spectrum Analysis of Interval Valued Neutrosophic Graph using MATLAB, Neutrosophic Sets and Systems, vol. 24, 2019, pp. 46-60.

[20]           S. Broumi, D. Nagarajan, A. Bakali, M. Talea, F. Smarandache, M.Lathamaheswari, J. Kavikumar: Implementation of Neutrosophic Function Memberships Using MATLAB Program, Neutrosophic Sets and Systems, vol. 27, 2019, pp. 44-52.  DOI: 10.5281/zenodo.3275355

[21]           R.E.Bellman, L.A. Zadeh, Decision making in a fuzzy environment, Manag. Sci. 17(1970)      141–164.

[22]           H.J. Zimmerman, Fuzzy programming and linear programming with several objective  Functions, Fuzzy Sets Syst. 1(1978)45–55.

[23]           H.Tanaka, K. Asai, A formulation of fuzzy linear programming based on comparison of fuzzy number, Control and Cybernet. 13(1984)185–194.

[24]           L.Campos ,J.L.Verdegay, Linear programming problems and ranking of fuzzy numbers, Fuzzy Sets Syst. 32(1989)1–11.

[25]           H.Rommelfanger, R. Hanuscheck, J. Wolf,  Linear programming with fuzzy objective, Fuzzy Sets Syst. 29(1989)31-48.

[26]           J. M. Cadenas ,  J. L. Verdegay, Using  Fuzzy Numbers  in  Linear  Programming, System.Man.Cybernetics.PartB: Cybernetics.IEEE Transactions on . 27(1997)1016-1022.

[27]           J.J. Buckley , T. Feuring, Evalutionary algorithm solution to fuzzy problems: Fuzzy linear programming, Fuzzy Sets Syst. 109 (2000) 35-53.

[28]           I.Ramik, M. Vlach, Fuzzy mathematical programming: a unified approach based on fuzzy relation.Fuzzy Optim. Decis. Mak. 1(2002) 335–346.

[29]           W.A.Lodwick,K.A. Bachman,  Solving large-scale fuzzy and possibilistic optimization problems. Fuzzy Optim. Decis. Mak. 4(2005), 257–278.

[30]           J.J.Buckley, A. Abdalla, Monte Carlo methods in fuzzy queuing theory. Soft Comput. 13,(2009)1027–1033.

[31]           Edalatpanah, S. A., and S. Shahabi. "A new two-phase method for the fuzzy primal simplex  algorithm." International Review of Pure and Applied Mathematics 8, no. 2 (2012): 157-164.

[32]           H.  R. Maleki, M. Tata , M. Mashinchi,  Linear  Programming  with  Fuzzy Variables,  Fuzzy Sets Syst.  109 ( 2000 ) 21-33.

[33]           J. Ramik, Duality in Fuzzy Linear Programming: Some New Concepts and Results, Fuzzy Optim. Decis. Mak.  4 ( 2005 ) 25-39. 

[34]           K.  Ganesan  ,P.  Veeramani,  Fuzzy  Linear  Programs  with  Trapezoidal  Fuzzy Numbers,  Ann. Oper. Res. 143 ( 2006 )305-315.

[35]           N. Mahdavi-Amiri, S.H. Nasseri, Duality in fuzzy number linear programming by use of a  certain linear ranking function, Appl. Math. Comput. 180(2006) 206–216.

[36]            A. Ebrahimnejad, Sensitivity analysis in fuzzy number linear programming problems,  Math. Comput. Model. 53 (2011) 1878–1888.

[37]           S.M. Hashemi, M. Modarres, E. Nasrabadi, M.M. Nasrabadi, Fully fuzzified linear  programming, solution and duality, J. Intell. Fuzzy Syst. 17 (2006) 253–261.

[38]           T. Allahviranloo, F.H. Lotfi, M.K. Kiasary, N.A. Kiani, L. Alizadeh, Solving full fuzzy linear programming problem by the ranking function, Appl. Math. Sci.2 (2008) 19–32.

[39]           M. Dehghan, B. Hashemi, M. Ghatee, Computational methods for solving fully fuzzy linear systems, Appl. Math. Comput. 179 (2006) 328–343.

[40]           F.H. Lotfi, T. Allahviranloo, M.A. Jondabeha, L. Alizadeh, Solving a fully fuzzy linear programming using lexicography method and fuzzy approximate solution, Appl. Math. Modell. 33 (2009) 3151–3156.

[41]           A.Kumar, J. Kaur , P. Singh, A new method for solving fully fuzzy linear programming problems, Appl. Math. Modell. 35 (2011) 817-823.

[42]           H. Saberi Najafi, S.A. Edalatpanah, A Note on “A new method for solving fully fuzzy  linear programming problems”, Appl. Math. Modell. 37 (2013) 7865-7867.

[43]           J. Kaur , A.Kumar, Exact fuzzy optimal solution of fully fuzzy linear programming problems with unrestricted fuzzy variables, Appl .Intell. 37 (2012) 145-154.

[44]           Baykasoğlu, A., & Subulan, K. (2015). An analysis of fully fuzzy linear programming with  fuzzy decision variables through logistics network design problem. Knowledge-Based Systems, 90, 165-184.

[45]           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.

[46]           Najafi, H. S., Edalatpanah, S. A., & Dutta, H. (2016). A nonlinear model for fully fuzzy linear programming with fully unrestricted variables and parameters. Alexandria Engineering  Journal, 55(3), 2589-2595.

[47]           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.

[48]           Abdel-Baset M, Hezam IM, Smarandache F (2016). Neutrosophic goal programming. Neutrosophic Sets Syst 11:112–118.

[49]           Pramanik, S. (2016). Neutrosophic multi-objective linear programming. Global Journal of Engineering Science and Research Management, 3(8), 36-46

[50]           Abdel-Basset, M., Gunasekaran, M., Mohamed, M., & Smarandache, F. (2019). A novel method for solving the fully neutrosophic linear programming problems. Neural Computi and Applications, 31(5), 1595-1605.

[51]           Singh, A., Kumar, A., & Appadoo, S. S. A novel method for solving the fully neutrosophic  linear programming problems: Suggested modifications. Journal of Intelligent & Fuzzy  Systems, (Preprint), 1-12.