SRT-GA: Smart real-time system using a powerful genetic algorithm for school bus routing problem

Abstract

The School Bus Routing Problem (SBRP) is an optimization problem in which to seek for shortest path to collect the students and deliver them efficiently to the nominated school. In this paper, we present a new smart system to the SBRP problem using the powerful Genetic Algorithm. The GA algorithm has three main bio-inspired operators (mutation, crossover and selection), which are recently considered to be used in finding the high-quality result for solving the optimization and search problems like SBRP problem. In this study, the GA is developed with new powerful crossover operator called edge assembly crossover (EAX) to obtain the best and fastest route to solve the SBRP problem. Then, the final shortest tour is sent to the bus-driver via his smartphone application with a real-time and last updated map-locations, which called A Smart Real-Time system using GA algorithm (SRT-GA), for solving SBRP problem. The SBRP standard benchmark datasets are used in evaluation process. Our proposed SRT-GA system is compare with four methods from literature. These comparative results show that the proposed SRT-GA method outperforms the entire set of the comparative methods.