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A Hybrid of Differential Evolution and Genetic Algorithm for the Multiple Geographical Feature Label Placement Problem
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所属单位：School of Geosciences and Info-Physics
发表刊物：ISPRS International Journal of Geo-Information
关键字：label placement; discrete differential evolution; genetic algorithm
摘要：Label placement is a difficult problem in automated map production. Many methods have been proposed to automatically place labels for various types of maps. While the methods are designed to automatically and effectively generate labels for the point, line and area features, less attention has been paid to the problem of jointly labeling all the different types of geographical features. In this paper, we refer to the labeling of all the graphic features as the multiple geographical feature label placement (MGFLP) problem. In the MGFLP problem, the overlapping and occlusion among labels and corresponding features produces poorly arranged labels, and results in a low-quality map. To solve the problem, a hybrid algorithm combining discrete differential evolution and the genetic algorithm (DDEGA) is proposed to search for an optimized placement that resolves the MGFLP problem. The quality of the proposed solution was evaluated using a weighted metric regarding a number of cartographical rules. Experiments were carried out to validate the performance of the proposed method in a set of cartographic tasks. The resulting label placement demonstrates the feasibility and the effectiveness of our method.
合写作者：Fuyu Lu, Jiqiu Deng*, Shiyu Li, Hao Deng
论文类型：基础研究
文献类型：J
卷号：8
期号：5
页面范围：237
是否译文：否
发表时间：2019-05-21
收录刊物：SCI