A Novel Quantum Ant Colony Algorithm Used for Campus Path

Abstract

With the development of mobile Internet technology and smart mobile devices, campus path navigation as a new trend have taken more attention. In this paper, we propose a new method based on quantum ant colony algorithm for campus path navigation. Quantum evolution algorithm has high effectiveness for solving combinational optimization problem. We combine ant colony algorithm with quantum evolution algorithm and propose quantum ant colony algorithm. This new scheme makes quantum bit encoding for the pheromone in each path. Then we use quantum revolving doors and the optimal path to update pheromone, which can accelerate convergence speed. In order to avoid the search falling into local optimum, a quantum crossover strategy is designed to improve the population information structure. Finally, the experiment results show that the new algorithm can search the best solution with a fast speed, enhance the global optimization ability and greatly improve the effectiveness of solving the problem of campus path navigation.