Optimizing map labeling of point features based on an onion peeling approach


  • Wan D. Bae University of Wisconsin-Stout
  • Shayma Alkobaisi United Arab Emirates University
  • Sada Narayanappa Jeppesen, Inc.
  • Petr Vojtechovsky University of Denver
  • Kye Y. Bae Digipen Institute of Technology


cartography, GIS, computational geometry, automated map labeling, onion peeling, genetic algorithm, simulated annealing, hill climbing


Map labeling of point features is the problem of placing text labels to corresponding point features on a map in a way that minimizes overlaps while satisfying basic rules for the quality. This is a critical problem in the application of cartography and geographical information systems (GIS). In this paper we study the fundamental issues related to map labeling of point features and develop a new genetic algorithm to solve this problem. We adopt a method called convex onion peeling and utilize it in our proposed convex onion peeling genetic algorithm (COPGA) to efficiently manage map labels of point features. The proposed algorithm takes advantage of a convex onion peeling structure to achieve better map label initialization and to enhance the evolutionary process. The performance of the proposed algorithm was evaluated through extensive experiments on both synthetic and real datasets. In experiments with an implementation of our algorithm using OpenMap, the results show that our genetic algorithm, based on convex onion peeling, is an efficient, robust, and extensible algorithm for automated map labeling of point features.