Linear Layout of Cold Chain Logistics Distribution Path Based on Heuristic Algorithm
With the growing demand for fresh food products,the cold chain logistics industry has rapidly developed,and it leads to the dual challenges of improving delivery efficiency and reducing environmental pollution.This paper proposes a multi-objec-tive path planning model that aims to minimize transportation costs and carbon emissions while maximizing customer satisfac-tion.The model is based on a series of key assumptions,considering fixed costs,transportation costs,product damage costs,and customer satisfaction factors.An improved artificial bee colony algorithm combined with Q-learning technology,known as the QABC algorithm,is proposed to enhance the efficiency and accuracy of path planning.Compared with the multi-objective particle swarm optimization(MOPSO)algorithm,the QABC algorithm shows significant advantages in terms of cost savings,reduces carbon emissions,and improves customer satisfaction.The experimental results show that the proposed model provides a new decision support tool for cold chain logistics distribution and promote the green and sustainable development of the indus-try.
万方数据
维普
