an enhanced feasible value constraint for multiobjective optimization problems

In this talk, we explore the application of the feasible value constraint method for tackling multiobjective optimization problems (mops). although this technique appear promising, it faces notable limitations, including restrictions on objective functions and weight assignments, limited flexibility in handling constraints, and difficulties in evaluating proper efficiency. to address these issues, we propose an enhanced formulation of the feasible value constraint technique.