Modified γ-operator technique for intuitionistic fuzzy multi-objective nonlinear programming problems with application in agriculture

Abstract

In recent years, intuitionistic fuzzy theory has gained significant attention for its ability to handle uncertainty through both membership and non-membership degrees. This paper presents a novel modification to $\gamma$-operator technique by introducing distinct $\gamma$-operators for membership and non-membership functions to tackle intuitionistic fuzzy environment. The proposed technique is rigorously validated through the proof of relevant theorems that demonstrate its capability to derive efficient solutions for multi-objective nonlinear programming problems, where all parameters are represented as triangular intuitionistic fuzzy numbers. To elucidate the proposed technique, an illustrative example is presented. Furthermore, a comparative study with existing techniques is conducted, which highlights the superior performance of the proposed method. Finally, an application in the agriculture sector demonstrates the practical relevance and effectiveness of the proposed method in real-world scenarios.