Optimising Parcel Deliveries in London Using Dual-Mode Routing

Last-mile delivery operations are complex, and the conventional way of using a single mode of delivery (e.g. driving) is not necessarily an efficient strategy. This paper describes a two-level parcel distribution model that combines walking and driving for a single driver. The model aims to minimise the total travelling time by scheduling a vehicle's routing and the driver's walking sequence when making deliveries, taking decisions on parking locations into consideration. The model is a variant of the Clustered Travelling Salesman Problem with Time Windows, in which the sequence of visits within each cluster is required to form a closed tour. When applied to a case study of an actual vehicle round from a parcel carrier operating in London, savings of over 20% in the total operation time were returned over the current situation where 104 transactions from 99 consignees were being delivered to 57 stopping points

Enabling the freight traffic controller for collaborative multi-drop urban logistics: practical and theoretical challenges

There is increasing interest in how horizontal collaboration between parcel carriers might help alleviate problems associated with last-mile logistics in congested urban centers. Through a detailed review of the literature on parcel logistics pertaining to collaboration, along with practical insights from carriers operating in the United Kingdom, this paper examines the challenges that will be faced in optimizing multicarrier, multidrop collection, and delivery schedules. A “freight traffic controller” (FTC) concept is proposed. The FTC would be a trusted third party, assigned to equitably manage the work allocation between collaborating carriers and the passage of vehicles over the last mile when joint benefits to the parties could be achieved. Creating this FTC concept required a combinatorial optimization approach for evaluation of the many combinations of hub locations, network configuration, and routing options for vehicle or walking to find the true value of each potential collaboration. At the same time, the traffic, social, and environmental impacts of these activities had to be considered. Cooperative game theory is a way to investigate the formation of collaborations (or coalitions), and the analysis used in this study identified a significant shortfall in current applications of this theory to last-mile parcel logistics. Application of theory to urban freight logistics has, thus far, failed to account for critical concerns including (a) the mismatch of vehicle parking locations relative to actual delivery addresses; (b) the combination of deliveries with collections, requests for the latter often being received in real time during the round; and (c) the variability in travel times and route options attributable to traffic and road network conditions

Collaborative Parcels Logistics via the Carrier’s Carrier Operating Model

Parcel logistics in urban areas are characterized by many carriers undertaking similar activity patterns at the same times of day. Using substantial carrier manifest datasets, this paper demonstrates advantages from rival carriers collaborating using a “carrier’s carrier” operating model for their last-mile parcel logistics operations. Under these circumstances, a single carrier undertakes all the deliveries within a defined area on behalf of the carriers instead of them working independently. Modelling the daily delivery activity of five parcel carriers working over a 3.7 km2 area of central London, comprising around 3000 items being delivered to around 900 delivery locations, and consolidating their activity through a single carrier suggested that time, distance and associated vehicle emissions savings of around 60% could be achieved over the current business-as-usual operation. This equated to a reduction in the number of delivery vans and drivers needed from 33 to 13, with annual savings of 39,425 h, 176,324 km driven, 52,721 kg CO2 and 56.4 kg NOx. Reliance on vans and associated vehicle emissions could be reduced further by using cargo cycles alongside vans for the last-mile delivery, with estimated annual emissions savings increasing to 72,572 kg CO2 and 77.7 kg NOx. The results indicated that consolidation of items for delivery in this way would be especially beneficial to business-to-consumer (B2C) carriers whose parcel profiles comprise relatively small and light items. One of the key barriers to the wider take up of such services by individual carriers is the loss of individual brand identity that can result from operating through a carrier’s carrier

Innovative solutions in last mile delivery: concepts, practices, challenges, and future directions

In the last decade, e-commerce has been growing consistently. Fostered by the covid pandemic, online retail has grown exponentially, particularly in industries including food, clothing, groceries and many others. This growth in online retailing activities has raised critical logistic challenges, especially in the last leg of the distribution, commonly referred to as the Last Mile. For instance, traditional truck-based home delivery has reached its limit within metropolitan areas and can no longer be an effective delivery method. Driven by technological progress, several other logistic solutions have been deployed as innovative alternatives to deliver parcels. This includes delivery by drones, smart parcel stations, robots, and crowdsourcing, among others. In this setting, this paper aims to provide a comprehensive review and analysis of the latest trends in last-mile delivery solutions from both industry and academic perspectives (see Figure 1 for overview). We use a content analysis literature review to analyse over 80 relevant publications, derive the necessary features of the latest innovation in the last mile delivery, and point out their different maturity levels and the related theoretical and operational challenges

Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

Alongside the rise of ‘last-mile’ delivery in contemporary urban logistics, drones have demonstrate commercial potential, given their outstanding triple-bottom-line performance. However, as a lithium-ion battery-powered device, drones’ social and environmental merits can be overturned by battery recycling and disposal. To maintain economic performance, yet minimise environmental negatives, fleet sharing is widely applied in the transportation field, with the aim of creating synergies within industry and increasing overall fleet use. However, if a sharing platform’s transparency is doubted, the sharing ability of the platform will be discounted. Known for its transparent and secure merits, blockchain technology provides new opportunities to improve existing sharing solutions. In particular, the decentralised structure and data encryption algorithm offered by blockchain allow every participant equal access to shared resources without undermining security issues. Therefore, this study explores the implementation of a blockchain-enabled fleet sharing solution to optimise drone operations, with consideration of battery wear and disposal effects. Unlike classical vehicle routing with fleet sharing problems, this research is more challenging, with multiple objectives (i.e., shortest path and fewest charging times), and considers different levels of sharing abilities. In this study, we propose a mixed-integer programming model to formulate the intended problem and solve the problem with a tailored branch-and-price algorithm. Through extensive experiments, the computational performance of our proposed solution is first articulated, and then the effectiveness of using blockchain to improve overall optimisation is reflected, and a series of critical influential factors with managerial significance are demonstrated

BESTFACT Best Practice Handbook 3

The Best Practice Handbook (BPH) gives an overview about current concepts, strategies and actions in freight transport all over Europe. It is disseminating information on successful projects and practices to increase awareness and share experiences. It is enabling knowledge transfer and supporting transferability for best practices. The third and last Best Practice Handbook focuses on the work done over the entire project, with 157 inventory cases and 60 in-depth analyses. After four years of case collection a wide field of solutions is available. The main findings of the BESTFACT cases are cross-checked and summarised for each of the cluster topics. The consistent form of collection and information provision broadens the structural understanding of best practice cases. The synthesis of cases per topic shows that under consideration of barriers and framework conditions replicable impacts are achievable. Main editors are Martin Ruesch & Simon Bohne (Rapptrans) and Jacques Leonardi (UoW). Project leader is Marcel Huschebeck (PTV)

Quantifying and Visualizing City Truck Route Network Efficiency Using a Virtual Testbed: Models for an Urban Freight and Parcel Delivery Virtual Testbed in NYC

69A3551747119This project explored routing app designs that can be of use to NYC DOT in informing truck drivers in NYC. This involved developing a prototype app and engaging in a hackathon in Fall 2022 to refine the visualization of the routing data. Second, we leveraged public data to construct a synthetic population of trucks that can be incorporated into a multiagent simulation that allows for dynamic passenger and commercial vehicle interactions. The synthetic truck population, which includes schedules of trip chains for each individual truck, will be incorporated into MATSim-NYC (He et al., 2021). Third, we proposed a new model for predicting zonal residential parcel delivery volumes and VMT that is applicable to large-scale scenarios and validate such a model using data from New York City (NYC)

A new three phase method (SDP method) for the multi-objective vehicle routing problem with simultaneous delivery and pickup (VRPSDP)

Transportation service operators are witnessing a growing demand for bi-directional movement of goods. Given this, the following thesis considers an extension to the vehicle routing problem (VRP) known as the delivery and pickup transportation problem (DPP), where delivery and pickup demands may occupy the same route. The problem is formulated here as the vehicle routing problem with simultaneous delivery and pickup (VRPSDP), which requires the concurrent service of the demands at the customer location. This formulation provides the greatest opportunity for cost savings for both the service provider and recipient. The aims of this research are to propose a new theoretical design to solve the multi-objective VRPSDP, provide software support for the suggested design and validate the method through a set of experiments. A new real-life based multi-objective VRPSDP is studied here, which requires the minimisation of the often conflicting objectives: operated vehicle fleet size, total routing distance and the maximum variation between route distances (workload variation). The former two objectives are commonly encountered in the domain and the latter is introduced here because it is essential for real-life routing problems. The VRPSDP is defined as a hard combinatorial optimisation problem, therefore an approximation method, Simultaneous Delivery and Pickup method (SDPmethod) is proposed to solve it. The SDPmethod consists of three phases. The first phase constructs a set of diverse partial solutions, where one is expected to form part of the near-optimal solution. The second phase determines assignment possibilities for each sub-problem. The third phase solves the sub-problems using a parallel genetic algorithm. The suggested genetic algorithm is improved by the introduction of a set of tools: genetic operator switching mechanism via diversity thresholds, accuracy analysis tool and a new fitness evaluation mechanism. This three phase method is proposed to address the shortcoming that exists in the domain, where an initial solution is built only then to be completely dismantled and redesigned in the optimisation phase. In addition, a new routing heuristic, RouteAlg, is proposed to solve the VRPSDP sub-problem, the travelling salesman problem with simultaneous delivery and pickup (TSPSDP). The experimental studies are conducted using the well known benchmark Salhi and Nagy (1999) test problems, where the SDPmethod and RouteAlg solutions are compared with the prominent works in the VRPSDP domain. The SDPmethod has demonstrated to be an effective method for solving the multi-objective VRPSDP and the RouteAlg for the TSPSDP