A goal programming-based algorithm for solving multi objective optimization problems
提出一种新算法，先单独优化每个目标函数，再用目标规划最小化与设定目标的偏差，在案例中表现优于其他方法。
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 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.