Optimizing fuzzy nonlinear programming problems through effective ranking methods
نویسندگان
1 Department of Mathematics, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur 603203, India.
2 Department of Mathematics, The University of Alabama, Alabama, USA.
3 Department of Mathematics, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur 603203, India.
doi
10.22105/jfea.2025.449539.1424چکیده
This research addresses the challenges of Fuzzy Nonlinear Programming Problems (FNPPs), especially those with decision parameters defined by triangular fuzzy numbers. The methodology involves initially converting these fuzzy numbers into precise values through a robust ranking technique, improving subsequent analyses' clarity and practicality. Following this conversion, a crisp nonlinear programming problem is formulated to enable a more straightforward and deterministic approach. The Kuhn-Tucker conditions are then applied to systematically explore and analyze the problem space, identifying an optimal solution. This study delves into the intricacies of fuzzy nonlinear programming, integrating robust ranking and Kuhn-Tucker optimization to effectively solve complex issues in this domain.
