¹College of Computer Science, South-Central University for Nationalities, State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430074, China
²School of Life Science and Technology, “Image Processing and Intelligence Control” Key Laboratory of Education, Ministry of China Huazhong University of Science and Technology, Wuhan 430074, China

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Abstract—A route planning method based on gradient-field quantum genetic algorithm model was presented in this paper. It introduces the gradient field of a grid map to quantum genetic algorithm model and uses quantum genetic algorithm (QGA) to optimize the cost function of route planning. By combining the quantum characteristics with the capabilities of the large diversity of the population, as well as fast convergence rate and high global searching, the optimization of route was guided and realized in our method by using the genetic operators with the essential characteristics of quantum and the gradient information of a grid map. Experimental results demonstrated that our method further effectively improves the quick convergence and capability of searching the optimal route.

Index Terms—Route planning, gradient field, QGA.

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Cite: Yangguang Sun, Mingyue Ding, "Route Planning Based on Gradient-Field Quantum Genetic Algorithm Model," Journal of Software vol. 8, no. 10, pp. 2511-2516, 2013.