A Modified Novel Method for Solving the Uncertainty Linear Programming Problems Based on Triangular Neutrosophic Number
Subject Areas : Transactions on Fuzzy Sets and SystemsKshitish Mohanta 1 , Vishal Chaubey 2 , Deena Sharanappa 3 , Vishnu Mishra 4
1 - Department of Mathematic, Indra Gandhi National Tribal University, Madhya Pradesh, India.
2 - Department of Mathematics, Indra Gandhi National Tribal University, Madhya Pradesh, India.
3 - Department of Mathematics, Indra Gandhi National Tribal University, Madhya Pradesh, India.
4 - Department of Mathematics, Indra Gandhi National Tribal University, Madhya Pradesh, India.
Keywords:
Abstract :
[1] M. Abdel-Basset, M. Gunasekaran, M. Mohamed and F. Smarandache, A novel method for solving the fully neutrosophic linear programming problems, Neural Comput. and Applic., 31(5) (2019), 1595-1605.
[2] M. Abdel-Basset and M. Mohamed, Multicriteria group decision making based on neutrosophic analytic hierarchy process: Suggested modi cations, Neutrosophic Sets and Systems, 43 (2021), 247-254.
[3] W. Abdelfattah, A parametric approach to solve neutrosophic linear programming models, J. Inf. Optim. Sci., 42(3) (2021), 631-654.
[4] E. AboElHamd, H. M. Shamma, M. Saleh and I. El-Khodary, Neutrosophic logic theory and applications, Neutrosophic Sets and Systems, 41 (2021), 30-51.
[5] R. Ahmed, F. Nasiri and T. Zayed, A novel neutrosophic-based machine learning approach for maintenance prioritization in healthcare facilities, Journal of Building Engineering, 42(9):102480 (2021).
[6] K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20(1) (1986), 87-96.
[7] T. Bera and N. K. Mahapatra, An approach to solve the linear programming problem using single valued trapezoidal neutrosophic number, International Journal of Neutrosophic Science, 3(2) (2020), 54-66.
[8] S. Bharati and S. Singh, A note on solving a fully intuitionistic fuzzy linear programming problem based on sign distance, International Journal of Computer Applications, 119(23) (2015), 30-35.
[9] S. Broumi, A. Bakali, M. Talea, F. Smarandache and L. Vladareanu, Shortest path problem under triangular fuzzy neutrosophic information, 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA), 15-17 Dec., 2016, Chengdu, China, (2016), 169-174.
[10] S. K. Das and A. Chakraborty, A new approach to evaluate linear programming problem in pentagonal neutrosophic environment, Complex & intelligent systems, 7 (2021), 101-110.
[11] I. Deli and Y. Subas, A ranking method of single valued neutrosophic numbers and its applications to multiattribute decision making problems, International Journal of Machine Learning and Cybernetics, 8(4) (2017), 1309-1322.
[12] A. Ebrahimnejad and M. Tavana, A novel method for solving linear programming problems with symmetric trapezoidal fuzzy numbers, Applied mathematical modelling, 38 (2014), 4388-4395.
[13] S. Edalatpanah, A direct model for triangular neutrosophic linear programming, International journal of neutrosophic science, 1(1) (2020), 19-28.
[14] A. Ghanbari Talouki, A. Koochari and S. Edalatpanah, Applications of neutrosophic logic in image processing: A survey, Journal of Electrical and Computer Engineering Innovations (JECEI), 10(1) (2022), 243-258.
[15] A. N. Gani and K. Ponnalagu, A method based on intuitionistic fuzzy linear programming for investment strategy, Int. J. Fuzzy Math. Arch., 10(1) (2016), 71-81.
[16] T. Garai, S. Dalapati, H. Garg and T. K. Roy, Possibility mean, variance and standard deviation of single-valued neutrosophic numbers and its applications to multi-attribute decision-making problems, Soft Comput., 24 (2020), 18795-18809.
[17] Z. Khan, M. Gulistan, N. Kausar and C. Park, Neutrosophic rayleigh model with some basic characteristics and engineering applications, IEEE Access, 9 (2021), 71277-71283.
[18] K. Khatter, Neutrosophic linear programming using possibilistic mean, Soft Computing, 24(22) (2020), 16847-16867.
[19] A. Kumar, J. Kaur and P. Singh, A new method for solving fully fuzzy linear programming problems, Applied mathematical modelling, 35(2) (2011), 817-823.
[20] Y. Leung, Spatial analysis and planning under imprecision, Elsevier, Netherlands, (1988).
[21] F. H. Lot , T. Allahviranloo, M. A. Jondabeh and L. Alizadeh, Solving a full fuzzy linear programming using lexicography method and fuzzy approximate solution, Applied mathematical modelling, 33(7) (2009), 3151-3156.
[22] K. K. Mohanta, D. S. Sharanappa and A. Aggarwal, Eciency analysis in the management of covid19 pandemic in india based on data envelopment analysis, Current Research in Behavioral Sciences 2, 100063 (2021).
[23] A. Nagoorgani and K. Ponnalagu, A new approach on solving intuitionistic fuzzy linear programming problem, Applied Mathematical Sciences, 6(70) (2012), 3467-3474.
[24] M. Riaz, F. Smarandache, F. Karaaslan, M. R. Hashmi and I. Nawaz, Neutrosophic Soft Rough Topology and its Applications to Multi-Criteria Decision-Making, Neutrosophic Sets and Systems, 35(1) (2020), 198-219.
[25] S. K. Sidhu and A. Kumar, A note on solving intuitionistic fuzzy linear programming problems by ranking function, Journal of Intelligent and Fuzzy Systems, 30(5) (2016), 2787-2790.
[26] A. Singh, A. Kumar and S. Appadoo, A novel method for solving the fully neutrosophic linear programming problems: Suggested modi cations, Journal of intelligent & fuzzy systems, 37(1) (2019), 885-895.
[27] F. Smarandache, A unifying eld in logics: neutrosophy logic. Neutrosophy, Neutrosophic set, Neutrosophic probability and statistics, American Research Press, (2003).
[28] F. Smarandache and S. Pramanik, New trends in neutrosophic theory and applications, In nite Study, (2016).
[29] Q. Wang, Y. Huang, S. Kong, X. Ma, Y. Liu, S. Das and S. Edalatpanah, A novel method for solving multiobjective linear programming problems with triangular neutrosophic numbers, Journal of Mathematics, (2021).
[30] L. A. Zadeh, Fuzzy sets, Advances in Fuzzy Systems{Applications and TheoryFuzzy Sets, Fuzzy Logic, and Fuzzy Systems, (1996), 394-432.
[31] H. J. Zimmermann, Fuzzy programming and linear programming with several objective functions, Fuzzy sets and systems, 1(1) (1978), 45-55.
[32] H. J. Zimmermann, Fuzzy sets, decision making, and expert systems, Springer Science & Business Media, (1987).