Air freight demand models: An overview

A survey is presented of some of the approaches which have been considered in freight demand estimation. The few existing continuous time computer simulations of aviation systems are reviewed, with a view toward the assessment of this approach as a tool for structuring air freight studies and for relating the different components of the air freight system. The variety of available data types and sources, without which the calibration, validation and the testing of both modal split and simulation models would be impossible are also reviewed

National and international freight transport models: overview and ideas for further development

This paper contains a review of the literature on freight transport models, focussing on the types of models that have been developed since the nineties for forecasting, policy simulation and project evaluation at the national and international level. Models for production, attraction, distribution, modal split and assignment are discussed in the paper. Furthermore, the paper also includes a number of ideas for future development, especially for the regional and urban components within national freight transport models

Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty

The increasing volumes of road transportation contribute to congestion on road, which leads to delays and other negative impacts on the reliability of transportation. Moreover, transportation is one of the main contributors to the growth of carbon dioxide equivalent emissions, where the impact of road transportation is significant. Therefore, governmental organizations and private commercial companies are looking for greener transportation solutions to eliminate the negative externalities of road transportation. In this paper, we present a novel solution framework to support the operational-level decisions for intermodal transportation networks using a combination of an optimization model and simulation. The simulation model includes stochastic elements in form of uncertain travel times, whereas the optimization model represents a deterministic and linear multi-commodity service network design formulation. The intermodal transportation plan can be optimized according to different objectives, including costs, time and CO2e emissions. The proposed approach is successfully implemented to real-life scenarios where differences in transportation plans for alternative objectives are presented. The solutions for transportation networks with up to 250 services and 20 orders show that the approach is capable of delivering reliable solutions and identifying possible disruptions and alternatives for adapting the unreliable transportation plans

Analytical Modeling Framework to Assess the Economic and Environmental Impacts of Residential Deliveries, and Evaluate Sustainable Last-Mile Strategies

In the last decade, e‐commerce has grown substantially, increasing business‐to‐business, business‐to‐consumer, and consumer‐to‐consumer transactions. While this has brought prosperity for the e-retailers, the ever-increasing consumer demand has brought more trucks to the residential areas, bringing along externalities such as congestion, air and noise pollution, and energy consumption. To cope with this, different logistics strategies such as the introduction of micro-hubs, alternative delivery points, and use of cargo bikes and zero emission vehicles for the last mile have been introduced and, in some cases, implemented as well. This project, hence, aims to develop an analytical framework to model urban last mile delivery. In particular, this study will build upon the previously developed econometric behavior models that capture e-commerce demand. Then, based on continuous approximation techniques, the authors will model the last-mile delivery operations. And finally, using the cost-based sustainability assessment model (developed in this study), the authors will estimate the economic and environmental impacts of residential deliveries under different city logistics strategies.View the NCST Project Webpag

Scheduled service network design with synchronization and transshipment constraints for intermodal container transportation networks

In this paper we address the problem of scheduled service network design for container freight distribution along rivers, canals, and coastlines. We propose a new concise continuous- time mixed-integer linear programming model that accurately evaluates the time of occurrence of transportation events and the number of containers transshipped between vehicles. Given the transportation network, the eet of available vehicles, the demand and the supply of containers, the sailing time of vehicles, and the structure of costs, the objective of the model is to build a minimum cost service network design and container distribution plan that denes services, their departure and arrival times, as well as vehicle and container routing. The model is solved with a commercial solver and is tested on data instances inspired from real-world problems encountered by EU carrier companies. The results of the computational study show that in scheduled service networks direct routes happen more often when either the eet capacity is tight or the handling costs and the lead time interval increase. The increase of the same parameters leads to the decrease of the number of containers transshipped between vehicles

Assessing the future of air freight

The role of air cargo in the current transportation system in the United States is explored. Methods for assessing the future role of this mode of transportation include the use of continuous-time recursive systems modeling for the simulation of different components of the air freight system, as well as for the development of alternative future scenarios which may result from different policy actions. A basic conceptual framework for conducting such a dynamic simulation is presented within the context of the air freight industry. Some research needs are identified and recommended for further research. The benefits, limitations, pitfalls, and problems usually associated with large scale systems models are examined

A SIMULATION MODEL FOR MAPPING CARBON DIOXIDE EMISSIONS TO DEVELOP A GREEN LOGISTICS SYSTEM

The aim of this thesis is to develop a simulation tool that helps companies to track and re-evaluate the environmental impacts on their logistics systems. A discrete event based simulation model is used and developed in this thesis and it provides a simple and visible solution to map the carbon emission footprints and calculate carbon emission values throughout an outbound logistics distribution network. The total carbon emission level in a simplified logistics distribution system is primarily determined by the total transport distance and different emission factors which categorized by many other important parameters such as load factor, empty trip rate, batch size, vehicle type and fuel consumption rate and so on. By visualizing carbon emission footprints and understanding how the carbon emission values in different transport paths are accumulated in the whole distribution system, the developed simulation model helps supply chain and logistics planners to investigate their current logistics systems and identify improvement areas in their systems to lead a better and greener logistics design. Website-based simulation software is also purposed as future research recommendation for realistic industry use.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Characterising and Modelling Urban Freight in Developing Economies

Urban freight systems in developing countries present significant challenges due to their complexity. Authorities often have inadequate institutional structures, making it difficult to identify and implement relevant initiatives. This thesis aims to characterise the systems in developing economies and model freight demand using innovative approaches by considering new attributes, dimensions and alternatives. As a first modelling step, freight (trip) generation was improved by considering spatial and locational determinants, as freight activities are strongly related to spatial and locational characteristics of establishments. Spatial models were developed using a combined spatial autoregressive model (SAR) and geographically weighted regression (GWR) or multiscale GWR (MGWR) (GWR/MGWR-SAR model). This model accounted for non-linearity, spatial heterogeneity and spatial dependency and demonstrated significant improvements (R2 0.29-0.71, RMSE reduced by 71% and AIC value by 56%). Shipment size decisions related to the choice of truck type were strongly timedependent, with commodity type, activities at the trip end, truck body type and industry sector affecting the preferences. Freight demand, including shipment size choices, was influenced by economic fluctuations, with shipment size declining after an economic slowdown. In freight demand modelling, it is imperative to consider economic conditions, especially those in developing countries, which are often susceptible to strong economic fluctuations. The models were applied in ex ante testing of a policy restricting large trucks from entering a city centre, as commonly considered in many developing countries. In tests, the truck restriction was accompanied by single-tier and two-tier distribution systems. The results showed that the two-tier system had a slight advantage over the single-tier system regarding operational expenditure and emission levels. Truck restriction was generally counterproductive, even when accompanied by distribution systems with greater speed and efficiency. We conclude that the models enhance the accurate prediction of freight demand patterns. The ex ante evaluation of policy alternatives supports the decision-making process for urban freight systems of large cities in developing economies. The models allow considering relevant practical, local contextual conditions