Hybrid approach for optimizing on-the-fly web map generalization

Abstract The creation of the map on-the-fly becomes today an important domain in cartography. Thousands of the users need access to spatial data on the web specific to their needs. This requires generating a map in real time. Different approaches appeared for optimizing the on-the-fly generation maps, but those not suffice for guiding a powerful and efficient process. Thus, a new approach must be developed for optimizing the on-thefly generalization process according to the user needs. This paper describe a new approach that combines the multi agent system and the techniques of genetic algorithm which improved by Tabu search method (GATS). We introduced the TS into the genetic algorithm to refine the solutions space found by GA toward the optimum solution. This approach uses the multiple representation and cartographic generalization. KeywordsOn-the-fly maps generalization, Agent, Genetic Algorithm, Tabu Search, cartographic constraints, multiple representations.