Matching estável para tomada de decisão colaborativa na alocação de slots

Collaborative Decision Making (CDM) is an important paradigm in the process of Air Tra c Management (ATM). According to this paradigm, the exchange of information among the di erent entities result in the improved decisions for ATM. However, the construction of the slot allocation algorithms used in the Ground Delay Program (GDP) with CDM, does not address the current major stakeholders in the decision-making process. At the same time, some shortcomings in GDP have been reported in several studies over the last years. One of these problems is that the Compression algorithm in CDM not always calculates the stable results in the allocation of resources related to airport. These limits of the ATM performance can generate the dissatisfaction among the stakeholders. To solve these problems, this PhD thesis proposes a new solution for the slot allocation problem addressed in the Compression algorithm. This model, called DASLOT enables the treatment of existing stakeholders in the CDM, as well as the inclusion of a new participant, the airport management services. The proposed model uses the matching theory to create a market slots where the airlines and the airport managers are the players. These stakeholders in CDM have their strategic preferences in the allocation process. The new algorithm has been developed based on the Deferred Acceptance (DA) mechanism for two-sided matching markets. The case studies are conducted for evaluation the developed model with the real data from Tancredo Neves International Airport (SBCF) of 2014. All the scenarios and data have taken from the o cial website of the Brazilian Airport Infrastructure Company (INFRAERO). The analysis on hypothetical and actual scenarios indicates that DASLOT model allows the correct treatment of the preferences of all players in the market through a stable allocation. In addition, desirable characteristics inherited from the DA mechanism, such as stability in the allocation and control manipulation of the results, may lead stakeholders to get overall performances in the system. These results can be considered as the main scienti c and social contributions of this research.