A binary coded multi-parent genetic algorithm for shuttle bus routing system in a college campus

Genetic algorithm (GA) has been successfully applied for many numerical optimization problems in the history. Multi-parent genetic algorithm (MPGA) is an extended genetic algorithm which uses more than two parent as a crossover operator for reproduction. Since MPGA has been increasing its interest in the family of genetic algorithms, it becomes an interesting algorithm to improve the solutions better than the traditional genetic algorithm by using the number of parents more than two for solving shuttle bus routing system (SBRS). In this paper, we compare MPGA and the traditional GA for the problem of SBRS in the Thammasat University (Rangsit Campus), Thailand. MPGA with up to 20 parents are used to optimize the shuttle bus routes in the campus. The diagonal crossover is used to measure the performance for both MPGA and GA in the reproduction process. The results prove that using multiple parents yields better solution than the traditional GA for solving the problem of SBRS.