The revolution of technology and the rapid evolution of the digital world had a significant effect on the development and expansion of e-commerce.Last mile delivery,for which different app-based delivery services have ...The revolution of technology and the rapid evolution of the digital world had a significant effect on the development and expansion of e-commerce.Last mile delivery,for which different app-based delivery services have recently emerged,is a new area of research that is not thoroughly addressed.Delivery ser-vice is one of the supporting platforms of e-commerce.One of the delivery issues is that many customers experience difficulties in communicating and coordinating with the logistics companies responsible for the delivery service.This challenge is emphasized in this study which introduces a new system to facilitate communica-tion and coordination between customers and logistics companies by using one identity and one interface.This paper is a programming-based study,as the pro-posed system evaluates a website to serve logistics companies as well as designs an application(app)to serve the customers of logistics companies.Swift,a power-ful open-source and object-oriented programming language,and the mark-up language(HTML)were used to build the last mile delivery system.In addition,Firebase,a cloud-hosted real-time database built on Google infrastructure,were used to develop the system.By increasing the level of customer satisfaction and reducing delivery failure rates,this system will eventually increase the prosperity of e-commerce.展开更多
The article is about solving the last mile delivery problem in rural town or village. We want to test the drone’s potential in parcel delivery. The objectives are 1) to introduce the cluster and truck-drone in tandem...The article is about solving the last mile delivery problem in rural town or village. We want to test the drone’s potential in parcel delivery. The objectives are 1) to introduce the cluster and truck-drone in tandem delivery method, 2) to compare the new method with the traditional TSP method in aspect of truck running distance, energy using and time occupation. The parcel delivery demand is sparse, so it is not dense enough for a truck to carry on delivery. We try to identify the best route for the drone to deliver the goods. We use k-mean method to carry on clustering, then we use enumeration method to fulfill the centroids delivery, which comes from the depot. We design a model and calculate the energy, time and distance saving between drone using method(DTSP) and traditional TSP method. The drone attended delivery saves truck delivery distance, energy consumption and time.The truck running distance of DTSP method saves 91.87%, the truck running distance is shortened from 189.69 km to 15.4252 km. The DTSP method saves 90.45% of energy. The DTSP method brings a29.75% cutoff in time aspect when there are two drone in running. The research introduces the cluster and TSP combination method, which is a good way to carry on last mile delivery. The result shows a bright future for drone to attend parcel delivery. The e-commerce corporation can apply this method in practice.展开更多
This paper assesses the vehicle dynamics of a new cargo bike concept developed for euro pallet sized cargo. The cargo bike developed is for last-mile delivery. Different aspects of manoeuvrability and stability are ex...This paper assesses the vehicle dynamics of a new cargo bike concept developed for euro pallet sized cargo. The cargo bike developed is for last-mile delivery. Different aspects of manoeuvrability and stability are examined using a series of manoeuvres based on tests from the automotive industry combined with bicycle industry regulations. These manoeuvres objectively evaluate and determine the handling capabilities of the cargo bike concept. Those tests can be compared using the results of the benchmark vehicles. The results conclude the new cargo bike has proper vehicle dynamics above the majority of benchmark vehicles but there is still room for improvement.展开更多
Freight transportation in urban areas has increased significantly in a shorter period due to the widespread use of e-commerce, fast delivery, and population growth. Recently, a noticeable government initiative aimed a...Freight transportation in urban areas has increased significantly in a shorter period due to the widespread use of e-commerce, fast delivery, and population growth. Recently, a noticeable government initiative aimed at creating an effective, acceptable, and sustainable city logistics policy. This paper examines freight consolidation as a transportation strategy for optimizing last-mile delivery costs. Freight consolidation involves combining smaller shipments from various origins into a single, larger shipment for more efficient transportation to a common destination. This approach is particularly beneficial for last-mile delivery, where frequent deliveries of smaller quantities are frequently visible. Finally, we provide an illustrative example targeting urban freight stakeholders for practicing possible consolidation methodology. The result in the illustrative example shows that freight with 3-day consolidation, despite the delay penalty, is cheaper than daily shipping, and both are cheaper than 2-day consolidated shipping. The study will benefit urban businesses and freight services.展开更多
最后一公里路径优化是提高物流企业配送效率的关键问题。本研究将深度强化学习中求解组合优化的方法(Learning to Optimize,L2O)与遗传算法相结合,提出一种混合算法,以求解最后一公里路径优化问题。在L2O模块中,扩展了已有框架,引入时...最后一公里路径优化是提高物流企业配送效率的关键问题。本研究将深度强化学习中求解组合优化的方法(Learning to Optimize,L2O)与遗传算法相结合,提出一种混合算法,以求解最后一公里路径优化问题。在L2O模块中,扩展了已有框架,引入时间和剩余容量编码器,有效反映了问题的时间和容量约束。同时,遗传算法模块采用重启策略和采样概率调控,更充分地利用了L2O的网络信息。基于亚马逊实际业务数据构建测试集,计算结果表明,在同样的求解时间内,该算法优于Gurobi求解器和扩展的指针网络算法。展开更多
文摘The revolution of technology and the rapid evolution of the digital world had a significant effect on the development and expansion of e-commerce.Last mile delivery,for which different app-based delivery services have recently emerged,is a new area of research that is not thoroughly addressed.Delivery ser-vice is one of the supporting platforms of e-commerce.One of the delivery issues is that many customers experience difficulties in communicating and coordinating with the logistics companies responsible for the delivery service.This challenge is emphasized in this study which introduces a new system to facilitate communica-tion and coordination between customers and logistics companies by using one identity and one interface.This paper is a programming-based study,as the pro-posed system evaluates a website to serve logistics companies as well as designs an application(app)to serve the customers of logistics companies.Swift,a power-ful open-source and object-oriented programming language,and the mark-up language(HTML)were used to build the last mile delivery system.In addition,Firebase,a cloud-hosted real-time database built on Google infrastructure,were used to develop the system.By increasing the level of customer satisfaction and reducing delivery failure rates,this system will eventually increase the prosperity of e-commerce.
基金Supported by China Scholarship Council(201507090026)
文摘The article is about solving the last mile delivery problem in rural town or village. We want to test the drone’s potential in parcel delivery. The objectives are 1) to introduce the cluster and truck-drone in tandem delivery method, 2) to compare the new method with the traditional TSP method in aspect of truck running distance, energy using and time occupation. The parcel delivery demand is sparse, so it is not dense enough for a truck to carry on delivery. We try to identify the best route for the drone to deliver the goods. We use k-mean method to carry on clustering, then we use enumeration method to fulfill the centroids delivery, which comes from the depot. We design a model and calculate the energy, time and distance saving between drone using method(DTSP) and traditional TSP method. The drone attended delivery saves truck delivery distance, energy consumption and time.The truck running distance of DTSP method saves 91.87%, the truck running distance is shortened from 189.69 km to 15.4252 km. The DTSP method saves 90.45% of energy. The DTSP method brings a29.75% cutoff in time aspect when there are two drone in running. The research introduces the cluster and TSP combination method, which is a good way to carry on last mile delivery. The result shows a bright future for drone to attend parcel delivery. The e-commerce corporation can apply this method in practice.
文摘This paper assesses the vehicle dynamics of a new cargo bike concept developed for euro pallet sized cargo. The cargo bike developed is for last-mile delivery. Different aspects of manoeuvrability and stability are examined using a series of manoeuvres based on tests from the automotive industry combined with bicycle industry regulations. These manoeuvres objectively evaluate and determine the handling capabilities of the cargo bike concept. Those tests can be compared using the results of the benchmark vehicles. The results conclude the new cargo bike has proper vehicle dynamics above the majority of benchmark vehicles but there is still room for improvement.
文摘Freight transportation in urban areas has increased significantly in a shorter period due to the widespread use of e-commerce, fast delivery, and population growth. Recently, a noticeable government initiative aimed at creating an effective, acceptable, and sustainable city logistics policy. This paper examines freight consolidation as a transportation strategy for optimizing last-mile delivery costs. Freight consolidation involves combining smaller shipments from various origins into a single, larger shipment for more efficient transportation to a common destination. This approach is particularly beneficial for last-mile delivery, where frequent deliveries of smaller quantities are frequently visible. Finally, we provide an illustrative example targeting urban freight stakeholders for practicing possible consolidation methodology. The result in the illustrative example shows that freight with 3-day consolidation, despite the delay penalty, is cheaper than daily shipping, and both are cheaper than 2-day consolidated shipping. The study will benefit urban businesses and freight services.
文摘最后一公里路径优化是提高物流企业配送效率的关键问题。本研究将深度强化学习中求解组合优化的方法(Learning to Optimize,L2O)与遗传算法相结合,提出一种混合算法,以求解最后一公里路径优化问题。在L2O模块中,扩展了已有框架,引入时间和剩余容量编码器,有效反映了问题的时间和容量约束。同时,遗传算法模块采用重启策略和采样概率调控,更充分地利用了L2O的网络信息。基于亚马逊实际业务数据构建测试集,计算结果表明,在同样的求解时间内,该算法优于Gurobi求解器和扩展的指针网络算法。
