Using the metaheuristic methods for real-time optimization of dynamic school bus routing problem and an application

Abstract

The vehicle routing problem (VRP) is an optimisation issue that has been studied for more than 50 years with its numerous subfields. The optimisation of VRP over distribution and transportation systems leads to significant gains in cost and time. There are many metaheuristic methods developed for the solution of the problem; and it was observed that metaheuristic methods prove to produce more successful results compared to common heuristic methods. In this study, a mobile-supported visual application was developed using ant colony optimisation (ACO) and genetic algorithm (GA), which are among the metaheuristic methods for the dynamic school bus routing problem (DSBRP), one of the sub-problems of VRP. The ACO and GA methods were utilised via the application for bus routes of a school located in the province of Ankara and the performance of these methods were compared through the obtained results. It was observed that time and distance values of the routes of current school bus routes may be improved by these two methods.