考虑分散协作及数量折扣的双目标电动车辆路径优化  

Dual-objective Electric Vehicle Routing Optimization Considering Decentralized Collaboration and Quantity Discount

作　　者：王能民[1,2] 史玮璇 崔巍 张萌 WANG Nengmin;SHI Weixuan;CUI Wei;ZHANG Meng(School of Management,Xi’an Jiaotong University,Xi’an 710049,China;ERC for Process Mining of Manufacturing Services in Shaanxi Province,Xi’an 710049,China;School of Economics and Management,Xi’an Technological University,Xi’an 710021,China)

机构地区：[1]西安交通大学管理学院,陕西西安710049 [2]陕西省制造服务业过程挖掘工程研究中心,陕西西安710049 [3]西安工业大学经济管理学院,陕西西安710021

出　　处：《工程管理科技前沿》2024年第4期27-36,共10页Frontiers of Science and Technology of Engineering Management

基　　金：国家自然科学基金重大资助项目(72192830,72192834);国家自然科学基金重点资助项目(71732006);国家自然科学基金青年资助项目(72301205);陕西省教育厅重点科学研究计划资助项目(23JY037)。

摘　　要：当前传统燃油车辆造成了极大的空气污染和资源浪费,电动车辆和协作物流是降低碳排放、提高运输效率的有效途径。本文基于协作物流的思想,建立以运输利润最大及配送任务完成量最大为双目标,考虑分散协作及数量折扣的带时间窗电动车辆路径优化模型。设计将贪婪随机自适应搜索—进化邻域搜索(GRASP-ELS)混合算法与ε-约束法相结合的ε-约束混合进化算法,并通过算例对模型和算法进行测试。实验结果表明:所提出的算法优于多目标优化算法NSGA-Ⅱ;通过灵敏度分析给出管理启示。本文为分散协作情境下电动车辆配送优化提供方法借鉴与决策参考。The logistics industry is one of the main sources of global energy consumption and carbon emissions.The use of traditional fuel vehicles has caused significant carbon emissions and resource wastage.Electric vehicle(EV),in comparison,can reduce lifecycle carbon emissions by up to 47%,making their adoption for delivery purposes an effective strategy for lowering transportation carbon emissions.Moreover,collaborative logistics models enable different logistics stakeholders to share logistics resources and information,thereby enhancing the efficiency of EV transportation and reducing energy consumption.However,in reality,most enterprises are unwilling to share all information with competitors and prioritize their own interests over collective benefits,making it difficult to achieve optimal overall benefits.Thus,many companies prefer a decentralized collaboration model that involves sharing partial information.Based on this,this paper studies the optimization of electric vehicle routing within a decentralized collaborative framework.Drawing from real-world scenarios and existing research on decentralized collaboration,this paper adopts a platform-based order selection model.Transport companies participating in collaboration use a platform to select profitable delivery orders and complete delivery services for compensation.Orders that are unprofitable due to long distances or high marginal costs are submitted to the platform,where they are available for selection by other companies.In relevant studies,unit transportation costs are often set as fixed values,but due to the economies of scale in transportation,the actual unit costs tend to decrease as transportation volume increases.Consequently,this paper reflects a quantity discount strategy in the cost structure,making transportation fees a piecewise linear function of the total task volume.Additionally,in collaborative logistics,the number of customers served by a logistics company reflects its market share,which companies aim to maximize.Therefore,this paper optimize

关 键 词：电动车辆路径 协作物流 数量折扣 双目标优化 ε-约束混合进化算法 

分 类 号：C931[经济管理—管理学]