A Modified Evolutionary Algorithm for Generating the Cycling Training Routes

Abstract

We present a novel method for generating cycling training routes from geographical property graphs based on an Evolutionary Algorithm. The algorithm operators of crossover and mutation are adjusted for use in the Property Graph domain. Data fusion of geographical data from the OpenStreetMap, EU-DEM digital surface model, and existing training records is performed as a basis of the intersections-paths property graph. The proposed approach allows route generation based on their starting and ending points in the property graph and their distance and ascent. A property graph of all intersections and cycling roads is shown and generated for the regions of Podravje and Pomurje. The property graph used in the proposed algorithm’s feasibility demonstration is shown. This is done by presenting four different cases of routes generated with our algorithm. The algorithm allows for generating classic cycling routes of A to B nature, routes with more than two fixed points, and cyclical training routes. The research is concluded by offering further directions on route generation research.

Keywords

• Data mining
• sports training
• automatic generation of sports training
• evolutionary algorithms