基于改进蚁群算法的低碳冷链物流配送模型优化与应用

Optimization and Application of Low-Carbon Cold Chain Logistics Distribution Model Based on Improved Ant Colony Algorithm

实现持续低碳化发展是冷链物流技术创新与优化的重要方向。基于成本约束视角,将冷链物流存储、配运、交付诸环节的运营成本和碳排放成本纳入企业总成本目标函数,构建冷链物流配送路径优化模型,使用蚁群算法与遗传算法变异算子结合求解,提高了算法迭代收敛速度。以医药冷链物流配送为例进行算法仿真优化与分析,验证了降低物流成本与节能减排可协同优化,获得良好的经济效益。模型和算法对环境可持续视角下的冷链物流配送路径问题有理论和实践意义。

It is an important direction of the cold chain logistics technology innovation and optimization to maintain sustainable low-carbon development.A cold chain logistics distribution routes optimization model was constructed based on the cost constraints,which incorporated the operation cost and carbon emission cost of cold chain logistics storage,distribution and delivery and other links into the total enterprises cost objective function,the ant colony algorithm was combined with genetic algorithm mutation operator to improve the iterative convergence rate of the algorithm.The pharmaceutical cold chain logistics distribution was used as an example for algorithm simulation optimization and analysis,which verified that reducing the logistics cost and energy saving and emission reduction can be coordinately optimized to obtain good economic benefits.The model and algorithm have theoretical and practical significance for the cold chain logistics distribution routes from the perspective of environmental sustainability.