In order to solve the problem that the B2C electronic commerce logistics distribution optimization accuracy is not high, a new hybrid differential evolution and particle swarm optimization heuristic optimization algorithm based B2C e-commerce logistics distribution optimization was proposed. Firstly, the particle swarm population was used as auxiliary mutation operator to do the crossover operation with differential evolution algorithm population, resulting new generation that inherits the advantages of characteristics of parents, thus avoiding the single algorithm premature convergence and low convergence rate. Through simulation comparison with the other existing improved algorithm, the algorithm here can effectively escape from local minima, prevent premature convergence, and the convergence is fastest. The simulation showed the designed distribution scheme has the faster calculation speed and better convergence of the target value.
