E-commerce is still a strong growing segment with fierce competition among parcel delivery service providers. To stay ahead of the competitors innovation is necessary. Currently, parcels are being ...delivered with large delivery vans which will usually deliver single parcels to doorsteps of their customers. This so called ‘last mile delivery’ is the most expensive logistics activity. In the literature it is proposed that parcel lockers have high potential to save cost. In our paper a literature review on parcel lockers, 3 methods for analysis are described and the results of a case study are provided.
In spite of the growing literature on and relevance of vehicle-drone parcel delivery, the logistical impact of cyclic drone flights, in which a drone launches and lands at the same node (as opposed ...to distinct sites) while delivering to a customer in between, remains unclear. To assess the pertinence and logistical impact of drone cycles, we propose a variable neighborhood search (VNS) heuristic for the Traveling Salesman Problem with Drone (TSP-D), whereby a vehicle and its companion aerial drone are synchronously routed to deliver customer orders with the objective of minimizing the return time of both carriers to the depot. The key to the success of the proposed VNS is a two-phase intensification scheme. In the first phase, the VNS broadly explores the feasible space by temporarily limiting the scope of drone flights and rendezvous locations. In the second phase, two features are introduced to ensure a deeper exploration of the feasible space: (i) intervening visits to customers are allowed for the vehicle between the drone rendezvous (launch and re-collect) nodes and (ii) drone operations may include no cycles, single cycles, or multiple cycles. The VNS is powered by optimization models that may accommodate the diverse operational settings proposed in the TSP-D literature. Over a set of benchmark instances, the VNS improves upon the best-known results for 113/120 instances having up to 100 nodes with comparable computational effort to existing approaches. The VNS also reveals improvements of up to 1%–8% in delivery times when drone multi-cycles are permitted, over a test-bed of diverse customer topographies and instance sizes.
•A variable neighborhood search (VNS) heuristic for vehicle-drone routing is proposed.•The VNS focuses on the logistical impact of allowing cyclic drone flights.•After initial simplifications, the VNS increases coordination between carriers.•The VNS improves upon results for 113/120 benchmark instances.•Permitting single/multiple drone cycles yields routes that are 1%–8% shorter.•Results suggest single cycles may play a part in high-quality solutions.•The study also introduces an instance generation schema designed to yield cycles.
•The planning of locations for parcel lockers and their location-specific layout is combined into one optimization framework.•The methodological focus is on (mixed-)integer linear programming and ...Benders decomposition.•The proposed algorithms enable solving large-scale problem instances to proven optimality.•The results of a computational (case) study based on real-world data from Austria are presented.•The results show that using parcel lockers can support supply chain viability at the last-mile delivery tier.
The pandemic caused by the corona virus SARS-CoV-2 raised many new challenges for humanity. For instance, governments imposed regulations such as lockdowns, resulting in supply chain shocks at different tiers. Additionally, delivery services reached their capacity limits because the demand for mail orders soared temporarily during the lockdowns. We argue that one option to support supply chain viability at the last-mile delivery tier is to use (outdoor) parcel lockers through which customers can collect their orderings 24/7 while ensuring physical distancing. The location planning of such lockers is known to be of utmost importance for their success. Another important topic to address is that the design of the compartment structure of the parcel lockers should meet the (uncertain) customer demand for different commodities. Both of the latter planning issues are combined into one optimization problem in this article. The objective is to maximize a linear function (e.g., expected profits) of the covered demand, given a budget an operator is willing to invest. An integer linear programming formulation is proposed, and a reformulation based on Benders decomposition is derived. It is shown that the Benders cuts can be separated in linear time. The developed algorithms enable solving of large-scale problem instances demonstrated by a performance analysis of computational experiments. The impact of different problem parameters on the obtained solutions is demonstrated by a sensitivity analysis. A case study based on real-world data from Austria is presented. The results show that using parcel lockers can support supply chain viability at the last-mile delivery tier. Moreover, the relatively small investment cost yields promising returns. The results further indicate that small-sized and medium-sized compartments should be preferred over large and x-large ones in the parcel locker compartment design.
This paper proposes a new agent-based model (ABM) to explore different scenarios of e-commerce urban deliveries, comparing door-to-door deliveries with consolidation-based strategies. The ABM ...reproduces operation under different demand patterns and include the possible matching of customer systematic trips and collection/delivery points with small detour from the scheduled trip.
Several variables of the model can be changed in a parametric simulation environment, allowing to infer the level of convenience of consolidation strategies for the different actors involved. The model provides indicators able to take into account customer and logistics operator perspectives, and the impact of the service on the community. Results can give useful information to understand how to manage growing on-demand urban deliveries and to measure the impact of freight transport on city sustainability.
Stationary parcel lockers have established as useful delivery options, especially for those households where nobody is at home during typical parcel delivery times. However, having to move toward a ...locker, maybe after a tiring workday, can be inconvenient for customers. Mobile parcel lockers, especially when driving autonomously, can be positioned closer to the customers and thus seem as a logical next evolutionary step to reduce customer inconvenience. Until autonomous driving is finally realized, however, mobile parcel lockers depend on human-driven vehicles to reposition them, and this paper compares optional locker–vehicle–driver setups. In the most restrictive case, a parcel locker is fixedly mounted onto a vehicle and equipped with a dedicated driver. But a human driver can also be in charge of multiple lockers, so that the driver must travel, e.g., via public transport, between different lockers in order to reposition them. There are also first concepts without a fixed coupling of lockers that are only loaded onto their vehicles. Hence, a vehicle equipped with an automated handling mechanism can subsequently reposition multiple mobile locker modules between different parking positions. Based on the assumption that a given set of customers is to be serviced with a predefined service level, this paper provides a flexible heuristic multi-stage optimization approach that minimizes the total costs associated with each of these concepts. This algorithm is applied in a benchmark study to compare the alternative mobile parcel locker concepts, and our results reveal substantial differences among them. For instance, we show that mobile locker modules are very effective to provide better customer service (i.e., smaller walking distances and longer parking durations) at low cost
•We benchmark five different mobile locker concepts against stationary lockers.•Mobile lockers with autonomous driving and human drivers are compared.•A heuristic framework that can be applied to all locker concepts is introduced.•Service expectations and their impact on locker resources are investigated.
•We consider parcel lockers that can change their locations over the day.•This novel concept on the last mile is compared with stationary lockers.•We develop program based on network flow ...formulations.•It is shown that mobile lockers considerably reduce the locker fleet size.
To reduce congestion, environmental damage, and negative health impact in large urban areas plenty of novel concepts for last-mile distribution have been innovated in the recent years. The concept treated in this paper are mobile parcel lockers that are able to change their locations during the day, either autonomously or moved by a human driver. By relocating lockers their reach towards addressees also varying their whereabouts over the day can be increased. This paper optimizes the changing locations of lockers, such that customers are at some time during the planning horizon within a predefined range of their designated locker. Our aim is to minimize the locker fleet when satisfying all customers. We formulate the resulting mobile locker location problem and provide suited exact solution procedures. To asses the potential whether mobile lockers are a promising last-mile concept, worth the investment required to develop it to a market-ready solution, we benchmark the necessary fleet size of mobile lockers with the required number of their stationary counterparts. Our results show that considerable reductions are possible.
We have developed an augmented reality (AR) based system which keeps track of events during the parcel handling process for last-mile logistics. The system can retrieve and highlight the location of ...parcels in large piles with AR on the user's smartphone. A camera array automatically detects the parcels laid down manually by an operator. New parcels are scanned and parcel fingerprints are generated semi-automatically. The system can detect and track the known parcels by fingerprint and can further highlight the location of the parcel using 3D visual clues, directly on the smartphone of the operator.
Pick-Up Points (PUPs) represent an alternative delivery option for online purchases. Parcels are delivered at a reduced cost to PUPs and wait until being picked up by customers or returned to the ...original warehouse if their sojourn time is over. When the chosen PUP is overloaded, the parcel may be refused and delivered to the next available PUP on the carrier tour. This paper presents and compares forecasting approaches for the load of a PUP to help PUP management companies balance delivery flows and reduce PUP overload. The parcel life-cycle has been taken into account in the forecasting process via models of the flow of parcel orders, the parcel delivery delays, and the pick-up process. Model-driven and data-driven approaches are compared in terms of load-prediction accuracy. For the considered example, the best approach (which makes use of the relationship of the load with the delivery and pick-up processes) is able to predict the load up to 4 days ahead with mean absolute errors ranging from 3.16 parcels (1 day ahead) to 8.51 parcels (4 days ahead) for a PUP with an average load of 45 parcels.
Drones are a promising tool for parcel delivery, since they are cost-efficient and environmentally friendly. However, owing to the limited capacity of the on-board battery, their flight range is ...constrained. Thus, they cannot deliver some parcels if the customers are too far from the depot. To address this issue, this article proposes a novel method, in which a parcel delivery drone can "take" a public transportation vehicle and travel on its roof. The problem under consideration is how to make use of the public transportation network to route the drone between the depot and the customer. Compared to the currently available methods that use drones, the most important merit of this approach is a significant expansion of the delivery area. We construct a multimodal network consisting of public transportation vehicles' trips and drone flights. Because of the complexity of this multimodal network, we convert it to a simple network with a set of simple procedures. In the extended network, we formulate the shortest drone path problem that minimizes the return instant to the depot, subject to that the drone energy consumption on this path is no greater than the initial energy. We present a Dijkstra-based method to find the shortest drone path. Moreover, we extend the proposed method to the case with uncertainty, because the public transportation vehicles cannot exactly follow their timetables in practice. Simulation results are presented to demonstrate how the method works.
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