抄録
As systems become more complex, the evaluation criteria for optimizing them increase. This paper aims to develop a multi-objective hierarchical optimization method for solving optimization problems of large-scale systems. The proposed multi-objective hierarchical optimization method requires a method for evaluating the Pareto solution of the upper hierarchy using the Pareto optimal solution of the lower hierarchy. In this paper, we propose an index to improve the quality of the Pareto solution based on the number of optimal solutions that update the existing Pareto solution in the Pareto front of the upper hierarchy, which is created by integrating the Pareto solutions of the lower hierarchy. Furthermore, we evaluate the maximum or minimum value of the upper-level Pareto front as an indicator for improving the spread of Pareto solutions. The results show that using a numerical model, the proposed method achieves a wider Pareto front than the conventional method in a case study.
