In the wake of e-commerce and its successful diffusion in most commercial activities, last-mile distribution causes more and more trouble in urban areas all around the globe. Growing parcel volumes ...to be delivered toward customer homes increase the number of delivery vans entering the city centers and thus add to congestion, pollution, and negative health impact. Therefore, it is anything but surprising that in recent years many novel delivery concepts on the last mile have been innovated. Among the most prominent are unmanned aerial vehicles (drones) and autonomous delivery robots taking over parcel delivery. This paper surveys established and novel last-mile concepts and puts special emphasis on the decision problems to be solved when setting up and operating each concept. To do so, we systematically record the alternative delivery concepts in a compact notation scheme, discuss the most important decision problems, and survey existing research on operations research methods solving these problems. Furthermore, we elaborate promising future research avenues.
Last mile deliveries with unmanned aerial vehicles (also denoted as drones) are seen as one promising idea to reduce excessive road traffic. To overcome the difficulties caused by the comparatively ...short operating ranges of drones, an innovative concept suggests to apply trucks as mobile landing and take‐off platforms. In this context, the paper on hand schedules the delivery to customers by drones for given truck routes. Given a fixed sequence of stops constituting a truck route and a set of customers to be supplied, we aim at a drone schedule (i.e., a set of trips each defining a drone's take‐off and landing stop and the customer serviced), such that all customers are supplied and the total duration of the delivery tour is minimized. We differentiate whether multiple drones or just a single one are placed on a truck and whether or not take‐off and landing stops have to be identical. We provide an analysis of computational complexity for each resulting subproblem, introduce efficient mixed‐integer programs, and compare all cases with regard to their potential of reducing the delivery effort on the last mile.
•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 consider a novel last-mile concept relying on autonomous robots.•A novel scheduling problem for launching robots from trucks is derived.•Efficient solution procedures for this problem are ...provided.•We benchmark the novel concept with traditional truck deliveries.
To reduce the negative impact of excessive traffic in large urban areas, many innovative concepts for intelligent transportation of people and freight have recently been developed. One of these concepts relies on autonomous delivery robots launched from trucks. A truck loads the freight dedicated to a set of customers in a central depot and moves into the city center. Also on board are small autonomous robots which each can be loaded with the freight dedicated to a single customer and launched from the truck. Then, the autonomous robots move to their dedicated customers and, after delivery, autonomously return to some robot depot in the city center. The truck can replenish robots at these decentralized depots to launch further of them until all its customers are supplied. To assess the potential of this innovative concept, this paper develops scheduling procedures which determine the truck route along robot depots and drop-off points where robots are launched, such that the weighted number of late customer deliveries is minimized. We formulate the resulting scheduling problem, investigate computational complexity, and develop suited solution methods. Furthermore, we benchmark the truck-based robot delivery concept with conventional attended home delivery by truck to assess the potential of this novel last-mile concept.
•Order processing along a crane-supplied pick face is considered.•We formulate the novel SKU switching problem for this setting.•Complexity is proven and suited exact and heuristic procedures are ...proposed.•In a simulation study, we show the operational gains enabled by our methods.
This paper treats an order picking system where a crane continuously relocates stock keeping units (SKUs) in a high-bay rack subdivided into the bottommost picking level and the upper reserve area. The capacity of the pick face is not large enough to store all SKUs, so that the crane has to ensure that all SKUs demanded by a current picking order are timely provided and picker idle time is avoided. We aim at a processing sequence of picking orders and a SKU switching plan, i.e., an instruction when to exchange which SKUs in the picking level, such that an unobstructed order picking is enabled. Our problem is closely related to the tool switching problem of flexible manufacturing. Here, each job requires a subset of tools to be loaded into the tool magazine (with limited capacity) of a single flexible machine. We, however, show that an alternative objective function, i.e., minimizing the maximum number of switches between any successive job pair, is better suited in the warehouse context and even better results can be obtained by a multi-objective approach. Elementary complexity proofs as well as suited solution procedures are provided and we also address managerial aspects, such as the sizing of the pick face.
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 analyze the structure of deterministic problems matching supply and demand in a sharing environment.•We provide a classification of these optimization problems.•We provide an analysis of ...computational complexity of several problems.•We consider the case of sharing parking space and explore the potential contribution of solving deterministic problems.
The sharing economy, i.e., the cooperative consumption of goods and services offered by private households or companies via online market places, gains more and more attention. Most sharing platforms coordinate transactions by generating each consumer an individual list of suited and available resources to choose from. If plenty online requests arrive rather simultaneously and compete for the scarce shared resources, however, an optimization-based coordination of supply and demand promises much better matches (e.g., more satisfied requests). This paper focuses deterministic matching problems and provides a classification scheme for the resulting optimization problems occurring in different areas of the sharing economy. These matching problems vary, for instance, if immobile (e.g., parking space) or mobile resources (e.g., vehicles of a car sharing provider) are shared. With the help of this classification, we give a detailed overview on known and novel complexity results. Furthermore, we apply the example of sharing parking space and explore the potential contribution of deterministic matchings when applied in a dynamic, uncertain, and opportunistic environment.
•Employees deliver parcels in the vicinity of a distribution center after work.•They are compensated by parcel and expect a minimum compensation for detours.•Logic-based Benders decomposition solves ...instances with 100 parcels optimally.•Optimal matching is substantially better than simple decision rules.
Seeing the huge success of sharing platforms such as Uber, Lyft, and Airbnb, where owners of under-used assets are connected with users willing to pay for the use of these assets, it is not surprising that retailers aim to transfer the basic idea of the sharing economy to their last-mile deliveries. In crowdshipping, the under-used assets are transport capacities of private drivers and the users are the retailers aiming for additional and cost-efficient delivery capacities for their home deliveries. A major drawback of crowdshipping is that retailers can hardly guarantee their promised delivery services when subcontracting individuals. To avoid this problem, different retailers are establishing crowdshipping platforms offering a reward to the employees of their distribution centers for crowdshipping online orders on their way back from work. We investigate the resulting optimization problem for matching crowdshipping supply and demand in this context. We present an efficient exact solution procedure based on Benders decomposition, which maximizes the number of matched shipments while considering the employees’ minimum expected earnings per time unit. This procedure is shown to solve instances of real-world size before a work shift is over and the shipments have to be loaded into the trunks of the employees’ cars. Furthermore, we show the impact of crowdshipping on all main stakeholders and identify critical success factors.
•Processing multiple orders demanding the same products jointly is treated.•We provide a classification scheme of the resulting synchronization problems.•Complexity results for the vast majority of ...problem settings are obtained.•We gain insight on suited system setups.•We benchmark the gains of synchronization with alternative decision tasks.
Triggered by the great success of e-commerce, today’s warehouses more and more evolve to fully-automated fulfillment factories. Many of them follow the parts-to-picker paradigm and employ shelf-lifting mobile robots or conveyors to deliver stock keeping units (SKUs) to stationary pickers operating in picking workstations. This paper aims to structure and review the family of synchronization problems that arise in this environment: If multiple orders demanding the same SKU can be serviced jointly, then a more efficient picking process and a relief of the bin supply system can be achieved. This paper classifies the family of slightly varying synchronization problems arising with different workstation setups in alternative warehouses. This classification scheme is applied to analyze computational complexity, to systematically quantify the gains of alternative workstation setups, and to benchmark the performance gains of synchronization with those of other well-established decision tasks. Our results show that the right workstation setup can greatly improve throughput performance, so that the gains of synchronization can outreach those promised by other well-researched decision tasks.
To meet today’s ambitious order throughput targets, many distribution centers, especially those operated by online retailers, apply batching and zoning in their picker-to-parts warehouses. These ...order retrieval policies improve the pick density per tour by unifying multiple customer orders to larger pick lists and allow a parallelization of the picking process among multiple zones, respectively. The price for this is an additional consolidation stage, where picked products must be sorted according to customer orders, typically with the help of a sortation conveyor. In this context, we treat the loop sorter scheduling problem, which is defined as follows. Once a wave of orders, picked concurrently in multiple zones, has been inducted onto a closed-loop sorter, we have to assign the products that refer to the same stock keeping units (SKUs) to orders and orders to packing lanes, where they are prepared for shipping. Furthermore, we have to decide on the sequence in which the orders are channeled into their packing lanes. Our aim is to minimize the makespan until all orders of the current wave are readily sorted. We formulate the loop sorter scheduling problem, investigate computational complexity, and derive suitable solution algorithms. One important finding of our computational study is that simple priority rules, which are frequently applied in real-world warehouses and previous research, waste significant optimization potential.
•We treat the holistic loop sorter scheduling problem.•An analysis of computational complexity including all subproblems is provided.•Fast heuristics are introduced and tested in a static and dynamic environment.•We investigate managerial issues regarding the best sorter setup.
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