Research on Heterogenous Fleet Dynamic Vehicle Rounting Problem Based on Memetic Algorithm

Abstract

For the problem of heterogenous fleet dynamic vehicle rounting, a memetic algorithm was proposed to optimize the minimum vehicle number and transportation cost. In order to improve the global exploration ability of the algorithm, an improved distribution estimation algorithm is used in the pre-optimization phase of global search, Quantum genetic algorithm is used in real - time optimization. The client node reset and 2-opt algorithm are adopted to enhance the local search ability of the algorithm. Finally, the validity of the algorithm is verified by simulation experiments.