Matrix Games under an Intuitionistic Fuzzy Duality Approach with Exponential Functions: MRI-Related Cochlear Implant Analysis

Authors

DOI:

https://doi.org/10.31181/sdmap41202767

Keywords:

Two-person zero sum matrix game, Intuitionistic fuzzy goals, Exponential functions

Abstract

Game theory has evolved to incorporate various forms of uncertainty. The intuitionistic fuzzy (I-Fuzzy) framework is a powerful tool for modeling such uncertainties, particularly in two-person zero-sum matrix games (TZMGs) with imprecise goals. This study addresses TZMGs where goals are represented in I-Fuzzy form under pessimistic, optimistic, and mixed approaches. By applying exponential functions, optimization problems are constructed for each player. These problems are then transformed into crisp linear programming problems (LPPs) using logarithmic functions, enabling the derivation of optimal strategies. The role and impact of the shape parameter in exponential functions are analyzed, highlighting its influence through comparative insights. To illustrate the effectiveness and real-world relevance of the proposed approach, a practical healthcare problem evaluating adverse MRI effects on cochlear implant (CI) users is solved, showcasing both the methodology's applicability and its potential for decision-making under uncertainty.

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References

Neumann, J. v. (1928). Zur Theorie der Gesellschaftsspiele. Mathematische Annalen, 100(1), 295–300. https://doi.org/10.1007/BF01448847

Neumann, J. v., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press. https://doi.org/10.1515/9781400829460

Bauso, D. (2016). Game theory with engineering applications. Society for Industrial and Applied Mathematics (SIAM). https://doi.org/10.1137/1.9781611974690

Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

Campos, L. (1989). Fuzzy linear programming models to solve fuzzy matrix games. Fuzzy Sets and Systems, 32(3), 275–289. https://doi.org/10.1016/0165-0114(89)90260-1

Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3

Bector, C. R., Chandra, S., & Vijay, V. (2004). Duality in linear programming with fuzzy parameters and matrix games with fuzzy payoffs. Fuzzy Sets and Systems, 146(2), 253–269. https://doi.org/10.1016/j.fss.2003.10.005

Aggarwal, A., Mehra, A., & Chandra, S. (2012). Application of linear programming with I-fuzzy sets to matrix games with I-fuzzy goals. Fuzzy Optimization and Decision Making, 11(4), 465–480. https://doi.org/10.1007/s10700-012-9123-z

Aggarwal, A., Chandra, S., & Mehra, A. (2014). Solving matrix games with I-fuzzy payoffs: Pareto-optimal security strategies approach. Fuzzy Information and Engineering, 6(2), 167–192. https://doi.org/10.1016/j.fiae.2014.08.003

Kumar, S. (2016). Max-min solution approach for multi-objective matrix game with fuzzy goals. Yugoslav Journal of Operations Research, 26(1), 51–60. http://doi.org/10.2298/YJOR140415008K

Khan, I., Aggarwal, A., Mehra, A., & Chandra, S. (2017). Solving matrix games with Atanassov's I-fuzzy goals via indeterminancy resolution approach. Journal of Information and Optimization Sciences, 38(2), 259–287. https://doi.org/10.1080/02522667.2016.1164999

Kumar, S. (2017). The relationship between intuitionistic fuzzy programming and goal programming. In Proceedings of Sixth International Conference on Soft Computing for Problem Solving (Vol. 1, pp. 220–229). Springer. https://doi.org/10.1007/978-981-10-3322-3_20

Debnath, I. P., & Gupta, S. K. (2019). Exponential membership function and duality gaps for I-fuzzy linear programming problems. Iranian Journal of Fuzzy Systems, 16(2), 147–163. https://doi.org/10.22111/ijfs.2019.4549

Kumar, S. (2021). Piecewise linear programming approach to solve multi-objective matrix games with I-fuzzy goals. Annals of Operations Research, 8(1), 1–13. https://doi.org/10.1080/23307706.2019.1619491

Zheng, Z., & Brikaa, M. G. (2022). Solving multi-objective bi-matrix games with intuitionistic fuzzy goals through an aspiration level approach. International Journal of Computing Science and Mathematics, 16(4), 307–326. https://doi.org/10.1504/IJCSM.2022.128650

Naqvi, D., Verma, R., Aggarwal, A., & Sachdev, G. (2022). Solutions of matrix games involving linguistic interval-valued intuitionistic fuzzy sets. Soft Computing, 27(2), 783–808. https://doi.org/10.1007/s00500-022-07609-4

Seikh, M. R., & Dutta, S. (2024). A non-linear mathematical approach for solving matrix games with picture fuzzy payoffs with application to cyberterrorism attacks. Decision Analytics Journal, 10, Article 100394. https://doi.org/10.1016/j.dajour.2023.100394

Fujita, T., Mehmood, A., & Ghaib, A. A. (2025). Hyperfuzzy offgraphs: A unified graph-based theoretical decision framework for hierarchical under off-uncertainty. Applied Decision Analytics, 1(1), 1–14. http://ada-journal.org/index.php/ada/article/view/1

Kumar, S., & Garg, H. (2025). A novel two-level fuzzy set theoretic approach to solve multi-objective matrix games and its applications. Annals of Operations Research, 1–41. https://doi.org/10.1007/s10479-025-06524-9

Kumar, S., & Aashish. (2025). Archimedean T-norm and T-conorm based approach to solve q-rung orthopair fuzzy matrix games and its application to electric vehicle market share problem. In 7th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1–6). IEEE. https://doi.org/10.1109/ISCON65210.2025.11341405

Majid, S. S., Maleki, A., Basirat, S., & Golkafard, A. (2025). Fermatean fuzzy TOPSIS method and its application in ranking business intelligence-based strategies in smart city context. Journal of Operations Intelligence, 3(1), 1–16. https://doi.org/10.31181/jopi31202532

Malik, M., & Gupta, S. K. (2025). On optimistic, pessimistic and mixed fuzzy-programming based approaches to solve multi-objective fully intuitionistic fuzzy linear fractional programming problems. Annals of Operations Research, 346(2), 1399–1443. https://doi.org/10.1007/s10479-023-05173-0

Gupta, P., & Mehlawat, M. K. (2009). Bector-Chandra type duality in fuzzy linear programming with exponential membership functions. Fuzzy Sets and Systems, 160(22), 3290–3308. https://doi.org/10.1016/j.fss.2009.04.012

Angelov, P. P. (1997). Optimization in an intuitionistic fuzzy environment. Fuzzy Sets and Systems, 86(3), 299–306. https://doi.org/10.1016/S0165-0114(96)00009-7

Lin, A., Menta, A. K., Ahmed, S. A., Zhang, A., Perdomo, D., Reddy, A., & Ward, K. B. (2025). A comprehensive analysis of MRI-related cochlear implant adverse events reported by FDA's Manufacturer and User Facility Device Experience Database. Laryngoscope Investigative Otolaryngology, 10(1), e70073. https://doi.org/10.1002/lio2.70073

World Health Organization. (2025). Deafness and hearing loss. https://www.who.int/news-room/fact-sheets/detail/deafness-and-hearing-loss

World Health Organization. (2023). World Hearing Day. https://www.who.int/india/campaigns/world-hearing-day-2023

Indian Sign Language Research and Training Centre. (2011). About us. https://islrtc.nic.in/about-us/

Published

2026-03-14

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Articles

How to Cite

Kumar, S., Aashish, & Parashar, P. (2026). Matrix Games under an Intuitionistic Fuzzy Duality Approach with Exponential Functions: MRI-Related Cochlear Implant Analysis. Spectrum of Decision Making and Applications, 4(1), 1-23. https://doi.org/10.31181/sdmap41202767