Low-carbon logistics distribution route planning with improved particle swarm optimization algorithm

Abstract

By introducing a carbon emission calculation method, which considers the vehicle speed and load, a low-carbon logistics distribution route optimization model with the targets of minimizing the transport costs and carbon emissions is established. We propose a kind of improved particle swarm optimization algorithm to solve this model. Since the particle swarm optimization algorithm is easy to plunge into local optimum in its running late, the particle will conduct random mutation in the improved algorithm when it exceeds the maximum number of stagnations. The simulation results of the numerical example demonstrate that the new algorithm is effective and feasible.