Thesis. 1978. M.S.--Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERONAUTICS. / Includes bibliographical references. / M.S.

1. Problem one: Shipment planning in a dynamic environment. The planning of air cargo logistics is a complex endeavor that involves the collaboration of multiple logistics agents to deliver shipments in a timely, safe, and economic manner. Airfreight forwarders coordinate and manage shipments for their clients, and with the development of Internet logistics platforms, airfreight forwarders can now trade jobs and resources with other participants effectively. The incorporation of trading alternatives significantly complicates the shipment planning process. / 2. Problem two: e-services platform design. The need for business logistics starts with a buyer and a seller. It involves arrangements of materials/products moving from the seller to the buyer and payment flows from the buyer and the seller. When the logistics arrangements are not done by the buyer nor the seller but rather by a specialist, we call the specialist a 3rd party logistics (3PL) service providers. A typical logistics service/job involves many agents, for instance, forwarders, truckers, warehouse operators, carriers, etc. In the process, a lot of information will be shared and exchanged among the agents, the buyer and the seller. With the advancement of information technologies, an emerging trend is to have the business dealing, information sharing and even payment arrangement among the logistics agents, buyers and sellers done through e-services on the Internet. In this thesis, we propose a 4th party logistics (4PL) platform, which is an Internet environment to enable and facilitate 3PL providers collaboratively provide services to buyers and sellers. / The proposed platform is called 4PL platform because it facilitates the 3PL agents. To better serve its 3PL clients, the platform should be "neutral", meaning it will not provide logistics services competing with its clients. The 4PL platform will facilitate its clients through e-services. However, existing e-services technology only allows e-services to be provided to individual clients. The idea of providing e-service to collaborating clients is new. We called it the 3rd party e-Service. In this thesis, we have conceptualized and further defined the 3rd party e-Service. To realize the 3rd party e-Service, we have first proposed a 3rd party service-oriented architecture and then developed a set of new elements to the existing e-Service description technology. To prove the concept, the new architecture, and the new description technology, we put into action. Using the shipment planning model as an example, we are able to offer shipment planning e-service to collaborating agents on the Internet. / This dissertation studies two research problems in a 4th party logistics platform. / This study proposes a dynamic decision framework for air cargo shipment planning, within the dynamic environment of bidding and trading. The framework has three phases: estimation, trading, and execution. Planning in the phases proceeds iteratively until an acceptable plan is obtained and shipments are set and fulfilled. The optimization of shipment planning is formulated as a mixed 0-1 LP model from a portfolio point of view. Unlike the models in previous research, this model targets profit maximization and takes into account the decisions of job selection and resource selection, and can be solved using a Tabu-based approach. We also discuss the respective rules and strategies that would aid the decision-making processes in the framework. / Chen Gang. / "February 2006." / Advisers: Waiman Cheung; Chi Kin Leung. / Source: Dissertation Abstracts International, Volume: 67-11, Section: A, page: 4358. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 96-106). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

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Commercial aviation has become an integral part of modern society and enables unprecedented global connectivity by increasing rapid business, cultural, and personal connectivity. In the decades following World War II, passenger travel through commercial aviation quickly grew at a rate of roughly 8% per year globally. The FAA's most recent Terminal Area Forecast predicts growth to continue at a rate of 2.5% domestically, and the market outlooks produced by Airbus and Boeing generally predict growth to continue at a rate of 5% per year globally over the next several decades, which translates into a need for up to 30,000 new aircraft produced by 2025. With such large numbers of new aircraft potentially entering service, any negative consequences of commercial aviation must undergo examination and mitigation by governing bodies so that growth may still be achieved. Options to simultaneously grow while reducing environmental impact include evolution of the commercial fleet through changes in operations, aircraft mix, and technology adoption. Methods to rapidly evaluate fleet environmental metrics are needed to enable decision makers to quickly compare the impact of different scenarios and weigh the impact of multiple policy options. As the fleet evolves, interdependencies may emerge in the form of tradeoffs between improvements in different environmental metrics as new technologies are brought into service. In order to include the impacts of these interdependencies on fleet evolution, physics-based modeling is required at the appropriate level of fidelity. Evaluation of environmental metrics in a physics-based manner can be done at the individual aircraft level, but will then not capture aggregate fleet metrics. Contrastingly, evaluation of environmental metrics at the fleet level is already being done for aircraft in the commercial fleet, but current tools and approaches require enhancement because they currently capture technology implementation through post-processing, which does not capture physical interdependencies that may arise at the aircraft-level. The goal of the work that has been conducted here was the development of a methodology to develop surrogate fleet approaches that leverage the capability of physics-based aircraft models and the development of connectivity to fleet-level analysis tools to enable rapid evaluation of fuel burn and emissions metrics. Instead of requiring development of an individual physics-based model for each vehicle in the fleet, the surrogate fleet approaches seek to reduce the number of such models needed while still accurately capturing performance of the fleet. By reducing the number of models, both development time and execution time to generate fleet-level results may also be reduced. The initial steps leading to surrogate fleet formulation were a characterization of the commercial fleet into groups based on capability followed by the selection of a reference vehicle model and a reference set of operations for each group. Next, three potential surrogate fleet approaches were formulated. These approaches include the parametric correction factor approach, in which the results of a reference vehicle model are corrected to match the aggregate results of each group; the average replacement approach, in which a new vehicle model is developed to generate aggregate results of each group, and the best-in-class replacement approach, in which results for a reference vehicle are simply substituted for the entire group. Once candidate surrogate fleet approaches were developed, they were each applied to and evaluated over the set of reference operations. Then each approach was evaluated for their ability to model variations in operations. Finally, the ability of each surrogate fleet approach to capture implementation of different technology suites along with corresponding interdependencies between fuel burn and emissions was evaluated using the concept of a virtual fleet to simulate the technology response of multiple aircraft families. The results of experimentation led to a down selection to the best approach to use to rapidly characterize the performance of the commercial fleet for accurately in the context of acceptability of current fleet evaluation methods. The parametric correction factor and average replacement approaches were shown to be successful in capturing reference fleet results as well as fleet performance with variations in operations. The best-in-class replacement approach was shown to be unacceptable as a model for the larger fleet in each of the scenarios tested. Finally, the average replacement approach was the only one that was successful in capturing the impact of technologies on a larger fleet. These results are meaningful because they show that it is possible to calculate the fuel burn and emissions of a larger fleet with a reduced number of physics-based models within acceptable bounds of accuracy. At the same time, the physics-based modeling also provides the ability to evaluate the impact of technologies on fleet-level fuel burn and emissions metrics. The value of such a capability is that multiple future fleet scenarios involving changes in both aircraft operations and technology levels may now be rapidly evaluated to inform and equip policy makers of the implications of impacts of changes on fleet-level metrics.

The increase in the types of airspace users (large aircraft, small and regional jets, very light jets, unmanned aerial vehicles, etc.), as well as the very limited number of future new airport development projects are some of the factors that will characterize the next decades in air transportation. These factors, associated with a persistent growth in air traffic will worsen the current gridlock situation experienced at some major airports. As airports are becoming the major capacity bottleneck to continued growth in air traffic, it is therefore primordial to make the most efficient use of the current, and very often, underutilized airport infrastructure. This research thus proposes to address the increase in air traffic demand and resulting capacity issues by considering the implementation of operational concepts and technologies at underutilized airports. However, there are many challenges associated with sustaining the development of this type of airports. First, the need to synchronize evolving technologies with airports' needs and investment capabilities is paramount. Additionally, it was observed that the evolution of secondary airports, and their needs, is tightly linked to the environment in which they operate. In particular, sensitivity of airports to changes in the dynamics of their environment is important, therefore requiring that the factors that drive the need for capacity expansion be identified and characterized. Finally, the difficulty to evaluate risk and make financially viable decisions, particularly when investing in new technologies, cannot be ignored. This work thus focuses on the development of a methodology to address these challenges and ensure the sustainability of airport capacity-enhancement investments in a continuously changing environment. The four-step process developed in this research leverages the benefits yielded by impact assessment techniques, system dynamics modeling, and real options analysis to 1) provide the decision maker with a rigorous, structured, and traceable process for technology selection, 2) assess the combined impact of interrelated technologies, 3) support the translation of technology impact factors into airport performance indicators, and help identify the factors that drive the need for capacity expansion, and finally 4) enable the quantitative assessment of the strategic value of embedding flexibility in the formulation of technology portfolios and investment options. The proposed methodology demonstrates, through a change in demand at the airport modeled, the importance of being able to weigh both the technological and strategic performance of the technology portfolios considered. Hence, by capturing the time dimension and technology causality impacts in technology portfolio selection, this work helps identify key technologies or technology groupings, and assess their performance on airport metrics. By embedding flexibility in the formulation of investment scenarios, it provides the decision maker with a more accurate picture of the options available to him, as well as the time and sequence under which these should be exercised.

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published_or_final_version / abstract / toc / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

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The air transport sector is one that is particularly conducive to market dominance, and therefore to potential abuse thereof. Characterised, for several decades, by the omnipresence of barriers attributable to the preferential treatment enjoyed by undertakings under the sponsorship of their respective governments, European civil air transport has undergone progressive liberalisation over the years, under the auspices of the European institutions. / The object of the present thesis is to assess how the provisions of Article 82 of the E.C. Treaty have applied to the air transport sector prior and subsequent to deregulation, and how they remain indispensable, in the wake of emerging new factors that tend to keep the market of scheduled air services oligopolistic.