A goal programming-based algorithm for solving multi objective optimization problems

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 targets for further refinement. Through an ideal programming scheme, the algorithm minimizes deviations from these set goals. The proposed algorithm is used to solve a case study. The results derived from testing the algorithm demonstrate its superior performance relative to that of the other compared methods across all the objectives.