摘要
社区团购生鲜产品冷链配送具有碳排放高、客户点多等特点,同时受社区团购生鲜产品易变质属性的影响,社区团购配送问题是较为复杂的优化问题。文中以总成本最小为目标,构建了考虑碳排放的社区团购配送路径优化模型,并设计了灰狼优化算法求解,通过改进灰狼的参数更新公式、引入遗传算法变异策略,提高算法的有效性,获得全局最优解。最后通过实际算例进行求解,结果显示,文中建立的模型及设计的算法对解决社区团购低碳物流问题具有一定的实用性。
The cold chain distribution of community group-buying fresh products has the characteristics of high carbon emission,many customer points,etc.At the same time,affected by the perishable property of community group-buying fresh products,community group-buying distribution is a complicated optimization problem.Aiming at minimizing the total cost,a path optimization model of community group-buying fresh products distribution was constructed considering carbon emissions,and an improved Gray Wolf optimizer algorithm was designed for solution.Then,this paper improves the parameter update formula of Grey Wolf Optimizer algorithm,and introduces genetic algorithm variation strategy,aiming to improve the effectiveness of the algorithm and obtain the global optimal solution.Finally,a practical example is given to verify the effectiveness of the model and algorithm.The results show that the model established and the algorithm designed in this paper have certain practicability to solve the low-carbon logistics problem of community group-buying.
作者
张梦佳
朱涛
ZHANG Meng-jia;ZHU Tao(School of Management,Wuhan University of Science and Technology,Wuhan 430065,China)
出处
《物流工程与管理》
2024年第4期19-23,共5页
Logistics Engineering and Management
基金
湖北省教育厅科学技术研究计划青年人才项目“碳排放政策下多品种生鲜联合补货与配送协同优化研究”(Q20191102)。
关键词
社区团购
低碳物流
车辆路径问题
灰狼优化算法
community group-buying
low-carbon logistics
vehicle path problem
Grey Wolf Optimizer
