空間數據查詢像是最近鄰居與最佳位置查詢在文獻當中已被廣泛研究。在這篇論文中，我們提出一個多標準最佳位置查詢的迭代方法，這個迭代方法能應用在最佳位置選擇的更新問題。在提供關於更新問題的正式定義之後，我們提出一個增量更新的方法。這個方法以Minimum Overlapped Voronoi Diagram (MOVD) 新增刪除物件為基礎。除此之外，我們以數學來分析增量更新方法的複雜度。在效率評估上，我們的演算法是透過大量實驗數據來衡量。由結論可知，我們提出的演算法與最先進的解決方法相較之下，在點集合數量與物件種類少的時候，我們的演算法發揮較好執行效率。;Spatial queries such as nearest neighbor and optimal location queries have been extensively studied in the literature. In this thesis, we present an iterative approach to Multi-Criteria Optimal Location Queries which can be applied on the updating problem of the optimal location selection. After providing a formal definition of the updating problem, we propose an incremental updating approach based on insertion and deletion of an object to the Minimum Overlapped Voronoi Diagram (MOVD). In addition, we analyze the the complexity of our solution for the updating problem. The performance of our algorithm is evaluated through extensive experiments. The results show that our algorithm runs efficiently compared with the state-of-the-art solution when the size of the point sets and the number of types are small.
