Chaotic genetic algorithm for solving vehicle routing problems with time windows
求解带时间窗车辆路径问题的混沌遗传算法

Aiming at the disadvantage of big randomness and premature convergence in genetic algorithm, the paper put forward the chaotic genetic algorithms which was a combination of chaotic search technology and genetic algorithms to solve the vehicle routing problem with time windows VRPTW during the logistics and distribution. The algorithm mapped chaotic va-riables to the range of optimization variables and coded the getting variables to generate the initial population. Then, after the genetic operations, it increased chaotic disturbance to the excellent individuals, and promoted the convergence rate of populations' evolution and get the optional solution. Compared the calculation results with other algorithms show that when the algorithm solves the VRPTW problem, the search efficiency is high and it can converge in the optional solution in a fast speed and offers a new method to the VRPTW solving.