Abstract In multiobjective optimization scenarios, the challenge lies in balancing several conflicting objectives; classic optimization methods, which focus on a single measurable criterion, do not adequately address this issue. The existing approaches have aimed to improve the efficiency of solving such problems, but finding an optimal solution across multiple objectives remains complex. This paper proposes a new algorithm that first optimizes each objective function individually, using the resulting solutions as…