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

Xiangdong Jiang, Nai-Yuan Pa, Wen-Chang Wang, Tian-Tian Yang, Wen-Tsao Pan
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引用次数: 2

Abstract

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.
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基于k均值聚类和果蝇优化算法的地震救援中心选址与布局
本文综合考虑了应急救援的及时性和成本约束。根据从救援中心到灾难现场的运输成本和建立救援中心的成本,考虑黄金救援时间。考虑失去黄金救助时间造成的处罚成本,从而将时效性量化为成本的另一个维度。采用k -均值聚类算法和果蝇算法(FOA)对该问题进行求解。以使应急救援中心的建设成本、运输成本和处罚成本加权总和最小为目的,选择合适的地点建立应急救援中心。最后,比较了改进后的两种算法(RWFOA和MFOA)的优化性能。利用k均值聚类分析和FOA对原模型进行简化和求解,使其能够求解复杂问题。对比RWFOA和MFOA, MFOA的最优值更低。
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