A Modified Novel Method for Solving the Uncertainty Linear Programming Problems Based on Triangular Neutrosophic Number
الموضوعات : 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.
الکلمات المفتاحية: Ranking Function, linear programming problem, Triangular Neutrosophic Number, Nutrosophic Linear Programming Problem,
ملخص المقالة :
Generally, linear programming (LP) problem is the most extensively utilized technique for solving and optimizing real-world problems due to its simplicity and efficiency. However, to deal with the inaccurate data, the neutrosophic set theory comes into play, which creates a simulation of the human decision-making process by considering all parts of the choice (i.e., agree, not sure, and disagree). Keeping the bene ts in mind, we proposed the neutrosophic LP models based on triangular neutrosophic numbers (TNN) and provided a method for solving them. Fuzzy LP problem can be converted into crips LP problem based on the de ned ranking function. The provided technique has been demonstrated with numerical examples given by Abdelfattah. Finally, we found that, when compared to previous approaches, the suggested method is simpler, more efficient, and capable of solving all types of fuzzy LP models.
[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).