An application study on vehicle routing problem based on improved genetic algorithm

Abstract

The Vehicle Routing Problem of Logistics and Distribution is a hot and difficult issue in current field of combinatorial optimization, therefore this paper presents an improved genetic algorithm. The algorithm which applied the idea of Saving Algorithm to the initialization of groups, and improved algorithm on selection operator and cross operator, In the meantime, it proposes a new way to calculate the adaptive probability in the cross operator. In addition, it also introduces a novel CX crossover operator .By the way of simulating experiments of the Vehicle Routing Problem, it demonstrates that the improved genetic algorithm enhanced the ability of global optimization, moreover it can significantly speed up convergence efficiency. © 2013 Springer-Verlag.