Site Selection and Layout of Earthquake Rescue Center Based on K-Means Clustering and Fruit Fly Optimization Algorithm

This article comprehensively considers timeliness of emergency rescue and cost constraints. Based on the transportation costs from the rescue center to the disaster site and the cost of setting up the rescue center, golden rescue timeis taken into account. The penalty cost caused by losing the golden rescue time is considered, thereby quantifying timeliness as another dimension of cost. The problem is solved using K-means clustering algorithm and fruit fly algorithm (FOA). With the purpose of minimizing the weighted sum of construction costs, transportation costs and penalty costs of emergency rescue centers, suitable location is selected for establishment of emergency rescue center. Finally, modified two algorithms (RWFOA and MFOA) are compared in optimization performance. The K-means clustering analysis and FOA are used to simplify and solve the original model, which can solve complex problems. In comparison between RWFOA and MFOA, the optimal value of MFOA is lower.