【作者】 张岩；

【导师】 卢福强；

【作者基本信息】 东北大学 ， 控制科学与工程， 2023， 硕士

【摘要】 互联网技术以及电子商务的蓬勃发展,为物流企业带来了前所未有的发展机遇。但随着需求以及各种促销活动的不断增加,物流企业自身运力不足、短期成本高昂等问题屡见不鲜。因具有配送成本低、灵活性强,可以提高闲置资源的利用率等众多优势的众包配送因运而生。近年来,众多学者着眼于众包配送模式下的车辆路径优化问题,以及传统配送模式下的车辆路径优化问题,而对于将传统配送模式与众包配送模式相结合的混合众包配送的车辆路径优化问题研究较少,缺少模型以及算法等方面的进一步拓展研究,因此,本文重点对混合众包配送模式下的车辆路径优化问题进行研究,并将其与传统配送模式下的结果进行比较分析,主要的研究内容如下:(1)考虑顺路捎带的混合众包车辆路径优化问题研究。考虑到在众包配送中,有一种可进行“顺路捎带”的车辆,这类车辆的特点是可以在自己行驶的路线中顺路帮助配送货物。因此考虑将这类众包车辆与传统配送中的企业车辆相结合共同对货物进行配送,建立以总配送成本最小为目标的车辆路径规划模型。模型中考虑所用车辆为多车型、且进行多包裹配送。同时为鼓励众包车辆可以对多个客户点进行服务,考虑众包车辆的出发地与目的地,利用众包车辆的配送路线与原始路线的比值作为其薪酬的奖励系数。为对数学模型进行求解,引入非线性因子、自适应权重、模拟退火三种改进策略,设计了改进的鲸鱼退火混合算法(IWSHA)。最后,设计实验案例并求解,实验结果表明,与仅利用企业车辆进行配送的传统配送模式相比,利用混合众包车辆配送的模式,不论在配送成本还是在配送距离上,结果都最优;同时,为检验改进的鲸鱼退火混合算法(IWSHA)的性能,将其与其他算法的优化结果进行比较,结果证明IWSHA算法在求解混合众包车辆路径优化问题的可行性和有效性。(2)考虑货物类别的混合众包车辆路径优化问题研究。考虑到实际配送中,客户所需要的货物类别的不同,对于车辆的选择与配送有很大影响,为提高客户满意度,多中心联合配送成为解决多货物种类需求的有效方法。因此,通过考虑客户所需要的货物种类不同,同时考虑多个配送中心,利用混合众包车辆对货物进行配送,建立以总配送成本最小与总配送距离最短为目标的多目标函数优化模型。模型中考虑多货物类别、多配送中心、所用车辆为多车型、所有车辆进行多包裹配送。通过设计实验算例,利用IWSHA算法分别对仅利用企业车辆、仅利用众包车辆以及利用混合众包车辆进行配送的车辆路径优化模型进行求解。实验结果表明,将企业车辆与众包车辆相结合共同进行货物配送,能够更好的结合二者的优势,从节约配送成本与减少配送距离方面来看,效果更明显。同时,将IWSHA算法与其他算法的求解结果进行比较,实验结果表明,IWSHA算法精度更高,求得的目标函数值最佳,进一步说明了算法的有效性。更多还原

【Abstract】 The vigorous development of Internet technology and e-commerce has brought unprecedented development opportunities for logistics enterprises.However,with the increasing demand and various promotional activities,logistics enterprises themselves lack of capacity,high short-term costs and other problems are common.Crowdsourcing distribution has many advantages such as low distribution cost,strong flexibility and improved utilization of idle resources.In recent years,many scholars have focused on the vehicle routing optimization problem under the crowdsourcing distribution mode and the traditional distribution mode.However,there are few studies on the vehicle routing optimization problem of hybrid crowdsourcing distribution which combines the traditional distribution mode and the crowdsourcing distribution mode,and there is a lack of further research on the model and algorithm.Therefore,This paper focuses on the research of vehicle routing optimization under the mixed crowdsourcing distribution mode,and compares it with the results under the traditional distribution mode.The main research contents are as follows:(1)Research on routing optimization of hybrid crowdsourcing vehicles considering side haul.Consider that in crowdsourcing,there are vehicles that can "piggyback," which feature vehicles that can help deliver goods on their own route.Therefore,this kind of crowd-sourced vehicle is combined with enterprise vehicle in traditional distribution to jointly distribute goods,and a path planning model aiming at minimum total distribution cost is established.In the model,it is considered that the vehicle used is multi-type and multi-parcel distribution is carried out.At the same time,in order to encourage crowd-sourced vehicles to serve multiple customer points,the origin and destination of the crowd-sourced vehicles were considered,and the ratio between the distribution route and the original route of the crowd-sourced vehicles was used as the reward coefficient of their compensation.In order to solve the mathematical model,an improved whale annealing hybrid algorithm(IWSHA)was designed by introducing three improved strategies:nonlinear factor,adaptive weight and simulated annealing.Finally,an experimental case is designed and solved.The experimental results show that,compared with the traditional distribution mode which only uses enterprise vehicles for distribution,the hybrid crowdsourcing vehicle distribution mode has the optimal results in terms of distribution cost and distribution distance.Meanwhile,in order to test the performance of the improved whale annealing hybrid algorithm(IWSHA),it is compared with the optimization results of other algorithms.The results show that the IWSHA algorithm is feasible and effective in solving the hybrid crowd-sourced vehicle routing optimization problem.(2)Research on hybrid crowdsourcing vehicle routing optimization considering the category of goods.Considering the different categories of goods required by customers in actual distribution,the selection and distribution of vehicles have a great impact.In order to improve customer satisfaction,multi-center joint distribution has become an effective method to solve the needs of multiple types of goods.Therefore,by considering the different types of goods required by customers and multiple distribution centers at the same time,a hybrid crowdsourcing vehicle is used to distribute goods,and a multi-objective function optimization model with the minimum total distribution cost and minimum total distribution distance is established.In the model,multiple cargo categories,multiple distribution centers,multiple vehicle types and all vehicles are considered for multi-parcel distribution.Through the design of experimental examples,the IWSHA algorithm is used to solve the vehicle routing optimization models which only use enterprise vehicles,only use crowdsourcing vehicles and use mixed crowdsourcing vehicles for distribution.The experimental results show that the combination of enterprise vehicles and crowd-sourced vehicles for goods distribution can better combine the advantages of the two,and the effect is more obvious in terms of saving distribution cost and reducing distribution distance.At the same time,the results of IWSHA algorithm are compared with those of other algorithms.The experimental results show that IWSHA algorithm has higher accuracy and the optimal objective function value,which further demonstrates the effectiveness of the algorithm.更多还原