电动物流车与燃油物流车混用的扩展轴辐式快递网络设计优化--考虑充电排队的影响

Express industry is facing challenges because of environmental pollution and resource constraints. Electric vehicle brings new opportunities with low carbon emission, but due to its limited mileage etc., both electric vehicles and fuel vehicles will be mix-used. Mixed using will give global impact on the express network design decisions. on the basis of classic hub and spoke network, project explores PH queuing modeling and performance index derivation method to reveal the effects of charging queuing action on the decision of network design including both on strategy and operation, focus on the extended hub and spoke express network which is more practical and complex but rarely researched, we add the consideration of the type of charging and limitation of capacities (including hub and roads and charging stations) and network structure (ring and star shape) on the background of mixed using, four kind of nonlinear mixed integer programming model were firstly proposed which were used to achieve network designing joint decision between strategy and operation level of multivariate, in order to reduce the difficulty of solving large-scale, high-dimension, nonlinear and so on. The linear strategy, Lagrange relaxation strategy and hybrid heuristic algorithm (IAGA&SS, DE&SS) and a new algorithm of cloud platform based on distributed hybrid algorithm IGSD were provided as the whole solution.The expected results of the project can promote the innovation of the express industry and the sustainable development with low carbon emission and can help to develop large-scale nonlinear mixed integer programming.

电动物流车的应用为快递业应对环境污染和资源约束带来机遇，但因为运营成本较高、续航里程有限等局限，电动与燃油车型将呈现混用局面，车型混用对快递网络设计决策具有全局影响。在经典轴辐式网络（Hub and Spoke）基础上，项目探索PH型排队建模和性能指标推导方法，揭示充电排队对网络设计战略和运作决策的影响；以更实用更复杂而少有研究的扩展轴辐式快递网络为对象，增加车型混用下续航模式、能力限制（轴辐、道路和充电站）和网络结构（环形和星型）等新内涵，首次提出四类情景下能够实现网络设计战略与运作层面多维变量联合决策的非线性混合整数规划模型，为降低大规模、高维度、非线性等带来的求解困难，设计线性化策略、拉格朗日松弛策略、混合式启发算法（IAGA&SS、DE&SS）和基于云平台的分布式混合算法IGSD等新算法。项目预期成果可促进快递行业模式创新与低碳可持续发展，推动大规模非线性混合整数规划问题研究进展。

电动物流车由于在节能环保等方面的优势，在配送领域得到大力推广。然而，受限于电动车续航里程短、充电时间长等，实际运营中电动车与燃油车混合配送模式更为常见。基于该背景，本研究构建一套适应电动物流车与燃油物流车混合使用的快递扩展轴辐式配送网络设计优化理论与方法。包括：（1）充电站PH排队系统建模。将电动车辆排队等待充电过程抽象为具有一般随机性、状态相关性的多服务台排队系统，构建充电站的PH/PH/C_0/C及等效转化的PH/PH(x)/1/C排队模型。（2）轴福式网络中基于公共充电站模式的电动车与燃油车混合配送理论与方法。基于客户时间窗约束、车辆最大载重约束、车队规模约束、电动车续航里程约束以及电动车的充电行为，构建了基于充电站的带时间窗电动车与燃油车混用的快递配送整数规划模型，并设计了分支定价算法；考虑了充电站采取分时电价，且允许部分充电等行为，构建了基于充电站的考虑分时电价的带时间窗电动车快递配送优化模型，并设计了自适应大规模邻域搜索算法；结合了燃油车的碳排放的影响，构建了基于充电站的考虑分时电价、碳排放的带时间窗电动车与燃油车混合的快递配送优化模型，设计了混合自适应大规模邻域搜索算法；考虑动态客户需求、部分充电以及分时电价，构建了基于充电站的考虑分时电价和动态需求的电动车快递配送两阶段整数规划模型，并设计了改进的自适应大规模邻域搜索算法；考虑众包车辆，构建了基于充电站的考虑分时电价和动态需求的企业自有与众包车辆混用的电动车快递配送优化模型，并设计了自适应大规模邻域搜索-禁忌搜索混合算法。（3）轴福式网络中基于换电站模式的电动车与燃油车混合配送理论与方法。考虑企业自建换电站，建立了基于换电模式的带时间窗电动车与燃油车混合快递配送优化模型，对换电站选址与混合车队路径规划进行联合决策，设计了带有自适应选择机制的启发分支定价算法。研究成果能有效促进城市快递配送行业的低碳可持续发展。

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