A Neutrosophic Compromise Programming Technique to Solve Multi-Objective Assignment Problem with T2TpFNs

被引：0
作者：
Kamal M. [1 ]
Kaur P. [2 ]
Ali I. [1 ]
Ahmed A. [1 ]
机构：
[1] Department of Statistics and Operations Research, Aligarh Muslim University, Aligarh
[2] University Institute of Engineering and Technology, Panjab University, Chandigarh
来源：
Neutrosophic Sets and Systems | 2022年 / 51卷
关键词：
Assignment problem; Fuzzy goal programming; Intuitionistic fuzzy programming; Multi-objective optimization; Neutrosophic programming; Type-2 fuzzy logic;
D O I：
10.5281/zenodo.7135275
中图分类号：
学科分类号：
摘要：
Multi-objective assignment problems (MOAPs) emerge in a wide range of real-world scenarios, from everyday activities to large-scale industrial operations. In this study, a MOAP with fuzzy parameters is investigated, and the fuzziness is represented by a Type-2 fuzzy logic system. Because the T2FLS is more efficient in dealing with the uncertainty of a decision-making process, the current problem's many parameters are represented by Type-2 trapezoidal fuzzy numbers (T2TpFNs). T2TpFNs are first reduced to Type-1 fuzzy numbers, then to crisp numbers. Finally, the neutrosophic compromise programming technique (NCPT) is applied to produce a problem compromise solution. A numerical problem is used to demonstrate the validity and applicability of the NCPT for the current MOAP. Furthermore, a comparison of NCPT to other techniques such as FPT and IFPT shows its superiority. © 2022, Neutrosophic Sets and Systems. All Rights Reserved.
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页码：172 / 204
页数：32
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共 83 条
  • [1] Adiche C., Aider M., A hybrid method for solving the multiobjective assignment problem, J. Math. Model. Algorithms, 9, pp. 149-164, (2010)
  • [2] Aggarwal S., Ranjit B., Ansari A.Q., Neutrosophicmodeling and control, Computer and Communication Technology (ICCCT), 2010 International Conference, pp. 718-723, (2010)
  • [3] Angelov P.P., Intuitionistic fuzzy optimization, Notes Intuit. Fuzzy Sets, 1, 2, pp. 123-129, (1995)
  • [4] Angelov P.P., Optimization in an Intuitionistic fuzzy environment, Fuzzy Sets Syst, 86, (1997)
  • [5] Atanassov K.T., Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20, pp. 87-96, (1986)
  • [6] Bao C.P., Tsai M.C., Tsai M.I., A new approach to study the multiobjective assignment problem, WHAMPOA-An Interdisciplinary Journal, 53, pp. 123-132, (2007)
  • [7] Belhoul L., Galand L., Vanderpooten D., An efficient procedure for finding best compromise solutions to the multiobjective assignment problem, Comput.Oper. Res, 49, pp. 97-106, (2014)
  • [8] Bellman R., Zadeh L., Decision making in fuzzy environment, Manag.Sci, 17, 4, (1970)
  • [9] Biswas P, Pramanik S., Multiobjective assignment problem with fuzzy costs for the case of military affairs, Int. J. Comput. Appl, 30, pp. 7-12, (2011)
  • [10] Biswas A., De A.K., A unified method of defuzzification for type-2 fuzzy numbers with its application to multiobjective decision making, Granular Computing, 3, 4, pp. 301-318, (2018)
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