•Introduction of detailed energy demand model for drones.•Hovering and wind conditions affects range of parcel delivery drones seriously.•Simulation study on energy demand of electric and Diesel ...trucks as well as drones.•Electric trucks require least energy and produce least GHG emissions in most situations.•Drones are competitive in rather rural settings (large distances, low customer density).
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.
Drone logistics is considered as a disruptive business model reshaping logistics in the next decades. Most prominent potential advantages of drone delivery are cost savings, high speed, and high ...flexibility. Additionally, drones are also considered as a means of green transportation as they are electric vehicles which are potentially emission-free. To which extent these claimed potentials exist depends on the application scenario as well as the environmental and technological conditions. In this study a stationary drone delivery system is considered where parcels are delivered from a central depot to customers either by drone or electric truck. The minimal total energy consumption for serving all customers is determined when using only an electric truck or a mixed fleet of electric trucks and drones. In a simulation study the effects of structural characteristics (like numbers of customers and customer density) and environmental conditions (like wind speed and traffic conditions) on potential energy savings using drones are estimated. The results indicate that structural characteristics and environmental conditions heavily affect the energy saving potential of drones. In urban settings with high customer density, the energy saving potential is limited to at most 1% while in rural settings drones can help to save 5% of total energy. Under drone-favoring conditions like calm winds and heavy traffic, the energy saving potential can double.
•First study on multi-product pipeline scheduling with transition technologies.•Modeling of product transitions by interfaces and physical product separation.•Variant of Economic Lot Scheduling ...Problem applied for pipeline scheduling. Proposal of a heuristic for pipeline scheduling with batch size limits.
In chemical and petroleum industry pipelines are one of the most important means of transportation. However, flexibility of pipeline transport systems is limited by many restrictions. Therefore, the planning of pipeline operations is a crucial part of logistics management in these industries. A particularly challenging problem is the pipeline scheduling which is concerned with finding the sequences, times, and sizes of batch injections in pipeline systems. This paper specifically studies the underlying core scheduling problem by assuming a simple multi-product pipeline system. It is shown that finding a sequence of batches which minimizes stock holding and setup costs in the long run is an NP-hard scheduling problem, namely a variant of the economic lot scheduling problem (ELSP) with additional constraints. Therefore, a powerful heuristic for the sequence-dependent ELSP is adapted and extended to meet the requirements of the outlined pipeline scheduling problem. The application of the heuristic is illustrated by case studies from chemical and petroleum industry.
•Introduction of an integrated lot-sizing and storage selection problem.•Consideration of multiple suppliers with individual, total, and hybrid discounts.•Modelling of heterogeneous storage ...facilities.•Proposal of a powerful heuristic for solving realistic instances.
In this paper we consider the sourcing process of a production facility from the process industry. The production facility sources raw materials from a set of suppliers that offer different discount schemes. For storing raw materials, heterogeneous storage facilities can be used, which vary with respect to their associated costs and capacities. We formulate the corresponding planning problem of selecting suppliers and storage facilities as well as determining order quantities and transport flows under the discount schemes offered by the suppliers. For solving large problem instances, a heuristic based on kernel search is proposed and evaluated in a real world case study. The case study reveals that supplier selection and storage selection are highly interdependent decisions. By integrating both perspectives, significant savings can be generated. It turns out that single-sourcing is the dominant strategy for most raw materials. However, the selection of the optimal suppliers depends on both the prices offered by the suppliers as well as the associated logistics costs for transportation and stock-holding.
•Introduces a fixed-charge, multi-commodity rail inventory transportation problem.•Incorporation of product handling and rail capacity restrictions.•Proposal of heuristics based on rolling horizon ...decomposition.•Computational experiments based on case study inspired by real-world data.
Rail transports of raw and intermediate materials are cornerstones in chemical logistics. In this paper a multi-commodity rail inventory transportation planning problem for chemicals is proposed. The aim is to generate transportation plans for chemicals and rail cars such that product demands are fulfilled and total logistics cost is minimized. To solve the problem, heuristics based on a rolling-horizon decomposition are proposed. A case study illustrates the applicability of the heuristics. The results show that near-optimal solutions can be generated quickly by the heuristics. Thus, an instrument is offered to transport managers which helps them to optimize chemical logistics processes.
Among the economic sectors, mobility is showing significant environmental impacts, especially in the use phase of vehicles. By substituting fossil-fuelled propelling systems, environmental impacts ...such as the Global Warming Potential (GWP) can be reduced. The use of properly designed light electric vehicles (LEVs) significantly reduces further environmental impacts, as well as maintenance costs, which are relevant for a circular economy. For example, the use of low-voltage (42 V) propelling systems enables the maintenance of LEVs in a broader range of existing bicycle workshops. Regarding the environmental impacts, the described LCA results indicate the advantage of LEVs compared with EVs and ICVs, e.g., vehicle weight is found to be a main factor related to environmental impact for each type of vehicle. This implies a reduced need for battery capacity and lower emissions of particulate matter from tire and break abrasion. This study aims to present the application potential of LEVs and the related reduction in environmental impacts. Anonymised inventory lists of municipal vehicle fleets are analysed for quantifying the substitution potential of LEVs in specific use cases. For this purpose, the use phase of vehicles is analysed with a focus on product design for repair and recycling and supplemented by the results of a comparative environmental impact assessment of internal combustion engine vehicles (ICEVs), electric vehicles (EVs), and LEVs. The comparison is made on the premise of similar application requirements. These specifications are the ability of each of the vehicles to transport a maximum of three persons (driver included) or one driver and 250 kg of cargo in 3 m3 over a daily distance of 100 km in urban areas. On this basis, the municipal environmental benefits derived from substituting small vehicles in the form of ICEVs and EVs with LEVs are assessed. The results show that in the field of municipal mobility, a relevant number of conventional small vehicles can be substituted with LEVs. The environmental impacts in categories of the highest robustness level, RL I, that is, Global Warming Potential, fine dust emissions, and Ozone Depletion Potential, can be reduced by LEVs by 50% compared with EVs and by over 50% compared with ICEVs. The strong influence of vehicle weight on the abrasive conditions of tires and brakes is considerable, as shown by reduced fine dust emissions.
•Formulates an emission-oriented vehicle routing problem on a multigraph.•Detailed emission estimation using heterogeneous vehicles and traffic parameters.•Provides a tailored column generation ...procedure using a label correcting algorithm.•Computational study with road data from the traffic of the Berlin city.•Instances with 100 customers can be solved near-optimal in 90 seconds on average.
In this work, an emission-minimizing vehicle routing problem with heterogeneous vehicles and a heterogeneous road and traffic network is considered as it is typical in urban areas. Depending on the load of the vehicle, there exist multiple emission-minimal arcs for traveling between two locations. To solve the vehicle routing problem efficiently, a column generation approach is presented. At the core of the procedure an emission-oriented elementary shortest path problem on a multigraph is solved by a backward labeling algorithm. It is shown that the labeling algorithm can be sped up by adjusting the dual master program and by restricting the number of labels propagated in the sub-problem. The column generation technique is used to setup a fast heuristic as well as a branch-and-price algorithm. Both procedures are evaluated based on test instances with up to 100 customers. It turns out that the heuristic approach is very effective and generates near-optimal solutions with gaps below 0.1% on average while only requiring a fraction of the runtime of the exact approach.
•Formulates a VRP with path selection and heterogeneous vehicles.•Provides an algorithm to determine load-depended emission-optimal paths.•On average between 2 and 3 emission-optimal paths exist in ...real-world road networks.•About 4% GHG emissions can be saved by path selection in simple problem instances.
In this paper, we formulate an emission-minimizing vehicle routing problem with heterogeneous vehicles and give rise to the effects of path selection. We take into account different paths for traveling between two locations differing with respect to their emissions. Computational experiments with artificial and real-world data illustrate the effects of path selection by considering networks with different road types like urban roads and highways. The experiments suggest an emission saving potential of about 2–4%. We conclude that in reality a larger emission reduction potential exists when multiple paths are considered in transportation planning.
Marshalling yards are nodes in rail networks to sort railcars from incoming trains to outgoing trains. To built outgoing trains in the correct sequence, railcars are shunted by shunting locomotives. ...Thereby, green house gas emissions are emitted as those locomotives are usually diesel powered. As the planning of shunting operations is a very complex problem, heuristics, so-called sorting strategies, are applied in practice. In this paper the effects of practically relevant sorting strategies on green house gas emissions are studied in a rolling horizon model. The rolling horizon model is used in a simulation study to investigate the effects of sorting strategies and input parameters (like the number and composition of ingoing and outgoing trains) on green house gas emissions. The results indicate that for different parameter constellations, different emission-optimal sorting strategies exist. Thus, sorting strategy selection should be done carefully depending on the operational conditions at the shunting yards.
PDF
