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IEEE Internet Computing
A genetic algorithm approach to cartographic map generalisation
Computers in Industry - Special issue: Soft computing in industrial applications
Mesh simplification for building typification
International Journal of Geographical Information Science
Web service approaches for providing enriched data structures to generalisation operators
International Journal of Geographical Information Science
From concept to implementation: web-based cartographic visualisation with cartoservice
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II
Creating task-specific maps with map content transformations
Proceedings of the 1st ACM SIGSPATIAL International Workshop on MapInteraction
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In map generalization various operators are applied to the features of a map in order to maintain and improve the legibility of the map after the scale has been changed. These operators must be applied in the proper sequence and the quality of the results must be continuously evaluated. Cartographic constraints can be used to define the conditions that have to be met in order to make a map legible and compliant to the user needs. The combinatorial optimization approaches shown in this paper use cartographic constraints to control and restrict the selection and application of a variety of different independent generalization operators into an optimal sequence. Different optimization techniques including hill climbing, simulated annealing and genetic deep search are presented and evaluated experimentally by the example of the generalization of buildings in blocks. All algorithms used in this paper have been implemented in a web services framework. This allows the use of distributed and parallel processing in order to speed up the search for optimized generalization operator sequences.