Description:
Abstract In view of the issue of carbon emissions generated by vehicles in the distribution link of supply chain, a low carbon supply chain distribution model is established considering collaborative optimization of production scheduling and distribution paths, taking the carbon emissions of pure electric trucks at different speeds under the time-varying network as the key variable. In this model, firstly, it is considering constraints such as product type, customer demand time window, vehicle load rate, loading and unloading time and service time. Secondly, an improved ant colony algorithm, a hybrid algorithm combining simulated annealing algorithm with ant colony algorithm, is proposed to improve the ability of searching and jumping out of local optimum. Finally, through the simulation optimization and comparative analysis of a random numerical example, it is verified that it can effectively reduce carbon emissions in the process of distribution using collaborative optimization model of supply chain production and distribution with minimizing optimization of carbon emissions and total travel time under the time-varying network, and the effectiveness of the algorithm is also verified.