What does this research mean for the field?

A novel two-level optimization framework effectively solves single-objective and multi-objective intuitionistic fuzzy matrix games by establishing a connection between fractional programming and goal programming. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

Formulate pessimistic, optimistic, and mixed solution approaches within a two-level optimization framework to resolve single-objective and multi-objective intuitionistic fuzzy matrix games.

August 29, 2026International Journal of Computational Intelligence SystemsOpen Access

Three Solution Approaches for Single-objective and Multi-objective Intuitionistic Fuzzy Matrix Games: a Two-level Optimization Framework and its Applications

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Authors

SKSandeep KumarGalgotias University AAashish SMSaiful R. MondalKing Faisal University

Discussion

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Implication

Computational study demonstrates a two-level optimization framework for intuitionistic fuzzy matrix games, highlighting practical utility in drug effect neutralization and market strategy.

Key Points

Formulate pessimistic, optimistic, and mixed solution approaches within a two-level optimization framework to resolve single-objective and multi-objective intuitionistic fuzzy matrix games.
Modeled two-player zero-sum matrix games using intuitionistic fuzzy goals and payoffs with assumed linear membership and non-membership functions.
Developed a two-level optimization framework establishing an equivalence between fractional programming and nonlinear goal programming under a pessimistic approach.
Demonstrated the model using illustrative examples and tested implementation across two case studies: adverse drug effect neutralization and electric vehicle market competition.
Proved mathematically that each player's single-objective optimization problem under the pessimistic approach is equivalent to fractional programming, solvable via nonlinear goal programming.
Extended the two-level framework to resolve multi-objective matrix games containing intuitionistic fuzzy parameters.
Derived optimal player strategies successfully in real-world applications involving pharmaceutical side-effect neutralization and electric vehicle market share analysis.

Cite This Study

Kumar et al. (2026) studied this question.

synapsesocial.com/papers/6a9299088e5d7d1fc0c10cf2 https://doi.org/10.1007/s44196-026-01550-2

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August 29, 2026International Journal of Computational Intelligence SystemsOpen Access

Three Solution Approaches for Single-objective and Multi-objective Intuitionistic Fuzzy Matrix Games: a Two-level Optimization Framework and its Applications

View Full Paper

Ask AI

Bookmark

Authors

SKSandeep KumarGalgotias University AAashish SMSaiful R. MondalKing Faisal University

Discussion

Member takes

Implication

Computational study demonstrates a two-level optimization framework for intuitionistic fuzzy matrix games, highlighting practical utility in drug effect neutralization and market strategy.

Key Points

Formulate pessimistic, optimistic, and mixed solution approaches within a two-level optimization framework to resolve single-objective and multi-objective intuitionistic fuzzy matrix games.
Modeled two-player zero-sum matrix games using intuitionistic fuzzy goals and payoffs with assumed linear membership and non-membership functions.
Developed a two-level optimization framework establishing an equivalence between fractional programming and nonlinear goal programming under a pessimistic approach.
Demonstrated the model using illustrative examples and tested implementation across two case studies: adverse drug effect neutralization and electric vehicle market competition.
Proved mathematically that each player's single-objective optimization problem under the pessimistic approach is equivalent to fractional programming, solvable via nonlinear goal programming.
Extended the two-level framework to resolve multi-objective matrix games containing intuitionistic fuzzy parameters.
Derived optimal player strategies successfully in real-world applications involving pharmaceutical side-effect neutralization and electric vehicle market share analysis.

Cite This Study

Kumar et al. (2026) studied this question.

synapsesocial.com/papers/6a9299088e5d7d1fc0c10cf2 https://doi.org/10.1007/s44196-026-01550-2

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