基于客户分类和混合车型的绿色车辆路径优化  

Green Vehicle Route Optimization Based on Customer Classification and Hybrid Vehicles

作　　者：杨静 俞武扬[1] YANG Jing;YU Wuyang(School of Management,Hangzhou Dianzi University,Hangzhou 310018,Zhejiang,China)

机构地区：[1]杭州电子科技大学管理学院,浙江杭州310018

出　　处：《信息与管理研究》2023年第1期75-86,共12页Journal of Information and Management

摘　　要：由于严重的环境污染、石油资源短缺等问题,政府出台燃油汽车限行等一系列的相关政策。相对于燃油汽车,污染较小和能耗更低的电动汽车受到全社会各界人士的广泛关注。企业为寻求长期和可持续的发展,用有限的配送资源得到更大的利润,将客户分类和混合车型融入车辆路径问题。在限行政策下,根据客户的多属性特点,采用熵值法赋值指标权重,再聚类将客户分类,构建基于客户分类和混合车型的车辆路径优化模型,以固定成本、惩罚成本和运输成本最小为目标,针对这种问题,用一种遗传算法求解该模型。结合杭州某物流公司的实际案例,在不同方案下进行对比分析验证模型的有效性。Due to such serious problems as environmental pollution,rising prices and the shortage of oil resources,the government has introduced a series of related policies like restrictions on fuel.vehicles.Compared with fuel vehicles,electric vehicles with less pollution and lower energy consumption have drawn wide attention from people of all walks of life.For long-term and sustainable development,enterprises use limited distribution resources to obtain greater profits,and integrate customer classification and mixed models into vehicle routing problems.Under the driving restriction policy,and according to the multi-attribute characteristics of customers,the entropy method is used to assign index weights and reclustering to classify customers,and build a vehicle routing optimization model based on customer classification and mixed vehicle models,aiming at the minimum fixed cost,penalty cost and transportation cost.Then,for this problem,a genetic algorithm is used to solve the.model.With a case study of a logistics company in Hangzhou,a comparative analysis is carried out under different schemes to verify the validity of the model.

关 键 词：混合车型 客户分类 车辆路径问题 

分 类 号：C939[经济管理—管理学]