Generalized Intuitionistic Fuzzy Programming for Non-Linear Multiobjective Optimization using T-Norms and T-Conorms

In real-world scenarios, decision-makers are often faced with the problem of optimizing several conflicting objectives governed by non-linear functions. In such cases, non-linear multi-objective programming problems are an important tool. However, as such, these cannot incorporate the underlying imprecision and vagueness of data. Therefore, to better accommodate the associated ambiguity of realistic circumstances, uncertain non-linear multiobjective programming problems are used. To optimize multiple objectives together, a compromise or Pareto-optimal solution is obtained using intuitionistic fuzzy programming (IFP). Through this article, we attempt to extend this widely used technique by utilizing t-norms and t-conorms of fuzzy sets. The proposed method generalizes the prevalent IFP and provides a decision-maker-friendly approach. Afterwards, a numerical illustration is presented using the proposed methodology with various t-norms and t-conorms and then the results are compared amongst themselves as well as with several predominant studies.