“最后一公里”无人车配送发展现状及应用前景

新冠肺炎疫情防控期间,面对隔离医院或社区生活必需品和医疗物资的需求压力,无人配送系统因其"高效率"、"零感染"等特点,凸显了其在"最后一公里"末端配送服务链中的重要作用。本文梳理了城市"最后一公里"配送的主要特征,分析了疫情防控期间"最后一公里"配送的主要痛点,探讨了无人车配送优势及难点。在系统调研国内外"最后一公里"无人配送商业化进程以及疫情防控期间无人配送车小范围应用的基础上,总结整理了无人车配送的关键研究成果以及未来研究方向。最后探讨了"最后一公里"无人车配送的应用前景,以及落地的技术路径及发展趋势。     

Vehicle routing with roaming delivery locations

We propose the vehicle routing problem with roaming delivery locations (VRPRDL) to model an innovation in last-mile delivery where a customer’s order is delivered to the trunk of his car. We develop construction and improvement heuristics for the VRPRDL based on two problem-specific techniques: (1) efficiently optimizing the delivery locations for a fixed customer delivery sequence and (2) efficiently switching a predecessor’s or successor’s delivery location during the insertion or deletion of a customer in a route. Furthermore, we conduct an extensive computation study to assess and quantify the benefits of trunk delivery in a variety of settings. The study reveals that a significant reduction in total distance travelled can be achieved, especially when trunk delivery is combined with traditional home delivery, which has both economic and environmental benefits.     

Optimal solution to the vehicle routing problem by adopting a meta-heuristic algorithm

The delivery service provided by large-scale retailers continues to grow as online sales occupy an increasingly large share of the market. This study aims to tease out efficient vehicle scheduling times as well as optimal delivery routes by applying meta-heuristic algorithms. Monthly data on existing routes were obtained from a branch of Korea’s leading large-scale online retailer. The first task was to examine the status of existing routes by comparing delivery routes created using Dijkstra’s algorithm with existing delivery routes and their vehicle scheduling. The second task was to identify optimal delivery routes through a comparative analysis of the genetic algorithm and Tabu search algorithm, known for its superior applicability amongst other meta-heuristic algorithms. These findings demonstrate that the optimal vehicle routing problem not only has the potential to reduce distribution costs for operators and expedite delivery for consumers, but also the added social benefit of reduced carbon emissions.     

A multi‐objective approach to the parcel express service delivery problem

Parcel express service in many countries assumes door‐to‐door delivery of parcels and small packages in the fastest possible way. Delivery companies usually organize hub delivery networks, as flows between hubs are characterized by the economy of scale effect. At hubs, parcels are exchanged across vans, trucks, and planes. To organize parcel delivery in a specific region, the parcel delivery company must make appropriate decisions about the total number of parcel delivery hubs, their locations, and the allocation of demand for facilities' services to facilities. These issues are modeled in this paper as a multi‐objective problem. The model developed is based on compromise programming and genetic algorithms. We also demonstrate in the paper an interactive manner in which a defined problem can be solved. The proposed model could be implemented in large‐scale networks. The paper also shows a case study of parcel delivery service in Serbia. Copyright © 2013 John Wiley & Sons, Ltd.     

The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery

Once limited to the military domain, unmanned aerial vehicles are now poised to gain widespread adoption in the commercial sector. One such application is to deploy these aircraft, also known as drones, for last-mile delivery in logistics operations. While significant research efforts are underway to improve the technology required to enable delivery by drone, less attention has been focused on the operational challenges associated with leveraging this technology. This paper provides two mathematical programming models aimed at optimal routing and scheduling of unmanned aircraft, and delivery trucks, in this new paradigm of parcel delivery. In particular, a unique variant of the classical vehicle routing problem is introduced, motivated by a scenario in which an unmanned aerial vehicle works in collaboration with a traditional delivery truck to distribute parcels. We present mixed integer linear programming formulations for two delivery-by-drone problems, along with two simple, yet effective, heuristic solution approaches to solve problems of practical size. Solutions to these problems will facilitate the adoption of unmanned aircraft for last-mile delivery. Such a delivery system is expected to provide faster receipt of customer orders at less cost to the distributor and with reduced environmental impacts. A numerical analysis demonstrates the effectiveness of the heuristics and investigates the tradeoffs between using drones with faster flight speeds versus longer endurance.     

Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London

Growth in e-commerce has led to increasing use of light goods vehicles for parcel deliveries in urban areas. This paper provides an insight into the reasons behind this growth and the resulting effort required to meet the exacting delivery services offered by e-retailers which often lead to poor vehicle utilisation in the last-mile operation, as well as the duplication of delivery services in urban centres as competitors vie for business. A case study investigating current parcel delivery operations in central London identified the scale of the challenge facing the last-mile parcel delivery driver, highlighting the importance of walking which can account for 62% of the total vehicle round time and 40% of the total round distance in the operations studied. The characteristics of these operations are in direct conflict with the urban infrastructure which is being increasingly redesigned in favour of walking, cycling and public transport, reducing the kerbside accessibility for last-mile operations. The paper highlights other pressures on last-mile operators associated with managing seasonal peaks in demand; reduced lead times between customers placing orders and deliveries being made; meeting delivery time windows; first-time delivery failure rates and the need to manage high levels of product returns. It concludes by describing a range of initiatives that retailers and parcel carriers, sometimes in conjunction with city authorities, can implement to reduce the costs associated with last-mile delivery, without negatively impacting on customer service levels.     

Comparison of energy demands of drone-based and ground-based parcel delivery services

Drones are one of the most intensively studied technologies in logistics in recent years. They combine technological features matching current trends in transport industry and society like autonomy, flexibility, and agility. Among the various concepts for using drones in logistics, parcel delivery is one of the most popular application scenarios. Companies like Amazon test drones particularly for last-mile delivery intending to achieve both reducing total cost and increasing customer satisfaction by fast deliveries. As drones are electric vehicles, they are also often claimed to be an eco-friendly mean of transportation.In this paper an energy consumption model for drones is proposed to describe the energy demand for drone deliveries depending on environmental conditions and the flight pattern. The model is used to simulate the energy demand of a stationary parcel delivery system which serves a set customers from a depot. The energy consumed by drones is compared to the energy demand of Diesel trucks and electric trucks serving the same customers from the same depot.The results indicate that switching to a solely drone-based parcel delivery system is not worthwhile from an energetic perspective in most scenarios. A stationary drone-based parcel delivery system requires more energy than a truck-based parcel delivery system particularly in urban areas where customer density is high and truck tours are comparatively short. In rather rural settings with long distances between customers, a drone-based parcel delivery system creates an energy demand comparable to a parcel delivery system with electric trucks provided environmental conditions are moderate.     

Optimizing express parcel networks and delivery schemes subject to timeliness tolerances

The ‘first come first served’ (FCFS) strategy usually adopted by air express companies does not consider delivery time tolerances and induces underuse of some facilities. This study relaxes the time tolerances and tackles the issue of parcel deliveries and transport network design for an express delivery company. In other words, it determines simultaneously the route loops of company-owned cargo aircraft, the amount of cargo space chartered for each link and the parcel delivery paths. Using a case study in which parcels must be delivered between 14 cities served by the SF Air Express Company, we find that FCFS is not the best approach for minimizing costs and that express companies can optimize both their delivery schemes and networks subject to some relaxed time tolerances.     

Assessing Service Quality,Switching Costs and Customer Loyalty in Home‐Delivery Services in Taiwan

Abstract

This study empirically investigated service quality, switching costs and customer loyalty from home‐delivery services' customers' perceptive. With regard to service quality attributes, findings indicated that customers were most satisfied with ‘range of delivery’, followed by ‘seldom loses parcels’, ‘invoice accuracy’, ‘prompt and reliable collection’ and ‘delivery by due time’. They were least satisfied with competitiveness of price. A structural equation modelling (SEM) approach was employed to analyse the impact of service quality and switching costs on customer loyalty from customers' perspective. Results revealed that service quality positively influenced switching costs and customer loyalty, and switching costs had a positive effect on customer loyalty. Investigation of the moderating effect of switching costs on the relationship between service quality and customer loyalty indicated that it was significantly important. Theoretical and practical implications of the findings for firms providing home‐delivery services are discussed.     

道路客运小件快运车辆路径和调度研究

制约小件运输发展的瓶颈之一是站到站运输与客户门到门需求之间的矛盾,目前道路客运企业正大力发展门到门的取送货业务,但缺少一套切实可行的取送货运输组织调度方案,基于此,文章建立了考虑客户时效性需求的车辆路径调度数学模型并设计了一种改进的遗传算法进行求解。通过实例证明该算法可以求得满意解,为道路客运企业发展小件快运的"最后一公里"取送货服务提供运输组织调度方案参考。     

Measuring transport related CO2 emissions induced by online and brick-and-mortar retailing

We develop a method for empirically measuring the difference in transport related carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their transport CO₂ footprints by 84% when buying standard consumer electronics products.     

Carbon and energy footprints of electric delivery trucks: A hybrid multi-regional input-output life cycle assessment

Due to frequent stop-and-go operation and long idling periods when driving in congested urban areas, the electrification of commercial delivery trucks has become an interesting topic nationwide. In this study, environmental impacts of various alternative delivery trucks including battery electric, diesel, diesel-electric hybrid, and compressed natural gas trucks are analyzed. A novel life cycle assessment method, an environmentally-extended multi-region input-output analysis, is utilized to calculate energy and carbon footprints throughout the supply chain of alternative delivery trucks. The uncertainties due to fuel consumption or other key parameter variations in real life, data ranges are taken into consideration using a Monte Carlo simulation. Furthermore, variations in regional electricity mix greenhouse gas emission are also considered to present a region-specific assessment for each vehicle type. According to the analysis results, although the battery electric delivery trucks have zero tailpipe emission, electric trucks are not expected to have lower environmental impacts compared to other alternatives. On average, the electric trucks have slightly more greenhouse emissions and energy consumption than those of other trucks. The regional analysis also indicates that the percentage of cleaner power sources in the electricity mix plays an important role in the life cycle greenhouse gas emission impacts of electric trucks.     

A decomposition-based iterative optimization algorithm for traveling salesman problem with drone

This study investigates a new delivery problem that has emerged after the attempts of several e-commerce and logistics firms to deploy drones in their operations to increase efficiency and reduce delivery times. In this problem, a delivery truck that carries a drone on its roof serves customers in coordination with a drone. The drone is considered to complement the truck due to its cost-efficiency and ability to access difficult terrains and to travel without exposure to congestion. This study presents an iterative algorithm that is based on a decomposition approach to minimize delivery completion time. In the first stage of the proposed methodology, the truck route and the customers assigned to the drone are determined. In the second stage, a mixed-integer linear programming model is solved to optimize the drone route by fixing the routing and the assignment decisions that are made in the first stage. Beginning with the shortest truck route, the assignment and the routing decisions are iteratively improved. The solution times of our algorithm are compared with the solution times of the state-of-the-art formulations that are solved by CPLEX. The results demonstrate that our algorithm yields shorter solution times for the instances that we generated with the specified parameters. An optimization-based heuristic algorithm, which obtains solutions for medium-sized instances, is developed by reducing the feasible search area.     

The impacts of E-retail on the choice of shopping trips and delivery: Some preliminary findings

E-retail, like many other information technology-based activities (telecommuting, telemedicine etc.) offers a potential substitution of travel by telecommunications. Traditional shopping activities typically consist of a visit to a store in which product information is sought, and a decision on purchase is made. Pending that decision, the product is obtained and most often self-delivered by the consumer. Certain types of products are store-delivered to the consumer premises. In the face of E-retail, consumers can acquire information, make a purchase transaction and choose a delivery arrangement from a remote location. These options may result in a reduction of transport activity, as a delivery by the supplier is potentially more efficient than the traditional process. The current study presents a conceptual model of the decisions households make with regard to information gathering, purchase transactions and delivery mode. Data on revealed behavior and various socio-demographic and economic characteristics of shoppers was collected in the Tel-Aviv Metropolitan area in the summer of 2004.     

A range-restricted recharging station coverage model for drone delivery service planning

Unmanned Aerial Vehicles (UAVs) are attracting significant interest for delivery service of small packages in urban areas. The limited flight range of electric drones powered by batteries or fuel cells requires refueling or recharging stations for extending coverage to a wider area. To develop such service, optimization methods are needed for designing a network of station locations and delivery routes. Unlike ground-transportation modes, however, UAVs do not follow a fixed network but rather can fly directly through continuous space. But, paths must avoid barriers and other obstacles. In this paper, we propose a new location model to support spatially configuring a system of recharging stations for commercial drone delivery service, drawing on literature from planar-space routing, range-restricted flow-refueling location, and maximal coverage location. We present a mixed-integer programming formulation and an efficient heuristic algorithm, along with results for a large case study of Phoenix, AZ to demonstrate the effectiveness and efficiency of the model.     

Anticipating emission-sensitive traffic management strategies for dynamic delivery routing

Traffic pollution is an increasing challenge for cities. Emissions such as nitrogen dioxides pose a major health threat to the city’s inhabitants. These emissions often accumulate to critical levels in local areas of the city. To react to these critical emission levels, cities start implementing dynamic traffic management systems (TMS). These systems dynamically redirect traffic flows away from critical areas. These measures impact the travel speeds within the city. This is of particular importance for parcel delivery companies. These companies deliver goods to customers in the city. To avoid long delivery times and higher costs, companies already adapt their routing with respect to changing traffic conditions. Still, a communication with the TMS may allow anticipatory planning to avoid potentially critical areas in the city. In this paper, we show how communication between TMS and delivery companies results in benefits for both parties. To exploit the provided information, we develop a dynamic routing policy anticipating potential future measures of the TMS. We analyze our algorithm in a comprehensive case study for the TMS of the city of Braunschweig, Germany, a city often used as reference for a typical European city layout. We show that for the delivery company, integrating the TMS’ information in their routing algorithms reduces the driving times significantly. For the TMS, providing the information results in less traffic in the polluted areas.     

郑州地铁参与同城快递的SWOT分析

传统同城快递配送在占用道路资源的同时,呈现出时效性差、效率低、易造成污染等缺陷。为缓解城市交通压力,提高物流效率,本文提出了在城市地下空间中借助地铁来实现同城快递配送的构想,并结合郑州地铁实例,运用SWOT分析法探讨了郑州地铁参与同城快递配送的优势、劣势、机会与威胁,据以判断这种地铁物流模式的可行性,为未来城市物流发展提供依据。     

Performance analysis of crowd-shipping in urban and suburban areas

Transportation - Crowd logistics is a novel shipping concept where delivery operations are carried out by using existing resources, namely vehicle capacity and drivers from the crowd, thereby...     

The two-echelon time-constrained vehicle routing problem in linehaul-delivery systems

Most of the studies address issues relating to the delivery from satellites to customers, which is throughout the end part of the linehaul-delivery system. Differing from the long-term strategic problems including the two-echelon vehicle routing problem (2E-VRP), the two-echelon location routing problem (2E-LRP) and the truck and trailer routing problem (TTRP) which make location decisions in depots or satellites, the paper introduces a short-term tactical problem named the two-echelon time-constrained vehicle routing problem in linehaul-delivery systems (2E-TVRP) that does not involve location decisions. The linehaul level and the delivery level are linked through city distribution centers (CDCs) located on the outskirts of cities. The 2E-TVRP has inter-CDC linehaul on the first level and urban delivery from CDCs to satellites on the second level. Vehicle routes on different levels are interacted by time constraints. A mixed integer nonlinear programming model for the 2E-TVRP is put forward, and a mixed integer linear programming model is used as the benchmark model. The Clarke and Wright savings heuristic algorithm (CW) improved by a local search phase is adopted. The 2E-TVRP formulations and the heuristic algorithm are tested by using 140 randomly-generated instances with up to 10 CDCs and 500 satellites. The computational results indicate that the heuristic can effectively solve various instances of the 2E-TVRP.     

Logistics impacts of student online shopping – Evaluating delivery consolidation to halls of residence

Growth in online shopping has led to increased numbers of small delivery vehicles in urban areas leading to a range of negative externalities. Young people are significant generators of home deliveries and, when clustered in university halls of residence, can generate considerable freight traffic to one location. This paper explores the potential to consolidate these deliveries using an urban consolidation centre. Based on the case of Southampton, UK, data were compiled from three linked sources: a delivery audit of four halls of residence at the University of Southampton housing 5050 residents; annual package receipt records from Southampton Solent University halls (2294 residents); and an online shopping survey distributed to Southampton University students (486 responses). The results suggest that in cities with multiple higher education institutions (HEIs), where in excess of 8000 students live in halls, over 13,000 courier trips could be generated annually, delivering over 4000 m³ of packages. These could be consolidated onto fewer than 300 vehicles for an annual service cost of approximately £18 per student, reducing congestion, parking infringements and improving air quality. Analysis indicated student acceptance of a consolidated parcel service but operational challenges would include enforcement, performance risk, finance and delivery speed.