Using the Ant Colony Algorithm for Real-Time Automatic Route of School Buses

Tuncay Yigit and Ozkan Unsal

Department of Computer Engineering, Süleyman Demirel University, Turkey

Abstract: Transportation and distribution systems are improving with an increasing pace with the help of current technological facilities and additionally, the complexity of those systems are increasing. Vehicle routing problems are difficult to solve with conventional techniques. Improving routes used in distribution systems provides significant savings in terms of time and costs. In this paper, current routes in school buses, which is a sub-branch of vehicle routing problems, are optimized using the Ant Colony Optimization (ACO), which is a heuristic artificial intelligence algorithm. Developed software is used for recommending the most suitable and the shortest route illustrated on a map by taking the instantaneous student wait locations online. Results of this study suggest that the current routes can be improved by using the ACO.

Keywords: ACO, school bus routing, vehicle routing problems, mobile software.

Received December 30, 2013; accepted December 23, 2014