Hesitant intuitionistic fuzzy algorithm for multiobjective optimization problem

Every real-life optimization problem with uncertainty and hesitation can not be a single objective, consequently, class of multiobjective linear problems (MOLOP) appears in the literature. Further, experts assign values uncertain parameters, expert’s opinions about parameters are conflicting nature. There concerning methods based on fuzzy sets, or their other versions available literature that only covers partial hesitation, but hesitant intuitionistic sets provides collective understanding MOLOP under it also reflects better practical aspects decision-making MOLOP. In this context, paper defines membership function nonmembership to tackle parameters. Here, new solution called Pareto optimal is defined, some theorems stated proved. For MOLOP, we develop an iterative method, illustrative example shows superiority proposed method. And lastly, calculated results compared popular methods.