摘要
在考虑冷链配送客户满意度的基础上,以车辆载重、客户时间窗和冷链产品变质率为约束,构建在客户服务时间范围内以碳排放量最小为优化目标的冷链车辆路径优化模型。将信息素浓度上下限融入传统蚁群算法,并结合领域搜索加快收敛速度、提高算法全局搜索能力。通过实例仿真表明,在低碳冷链VRP问题的求解过程中,改进型蚁群算法能够以更高的效率搜索最优成本。模型同时满足企业经济及社会效益,在不同规模实验场景下取得良好的路径优化效果,验证了模型的有效优化能力。
On the basis of considering the low customer satisfaction of cold chain distribution, taking vehicle load, customer time window and cold chain product deterioration rate as constraints, a cold chain vehicle path optimization model with the minimum carbon emission as the optimization goal in the customer service time range was constructed. The upper and lower limits of pheromone concentration were integrated into the traditional ant colony algorithm, and the convergence speed and global search ability were improved by combining the neighborhood search strategy. Simulation results showed that the improved ant colony algorithm could search the optimal cost with higher efficiency in the process of solving VRP Problem. At the same time, the model satisfied the economic and social benefits of enterprises, achieved good path optimization effect in different scale experimental scenarios, and verified the effective optimization ability of the model.
作者
任腾
陈玥
向迎春
邢立宁
李思迪
REN Teng;CHEN Yue;XIANG Yingchun;XING Lining;LI Sidi(School of Transportation and Logistics,Central South University of Forestry and Technology,Changsha 410004,China;School of Tourism,Central South University of Forestry and Technology,Changsha 410004,China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2020年第4期1108-1117,共10页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(61773120)
中南林业科技大学2018科技创新基金资助项目(11180086)
北京市智能物流系统协同创新中心开放资助项目(BILSCIC-2019KF-25)。
关键词
冷链物流
低碳经济
客户满意度
车辆路径问题
路径优化
cold chain logistics
low-carbon economy
customer satisfaction
vehicle routing problem
path optimization
