Abstract

This thesis aims to propose an optimization and improvement plan for the cab problem in airports. In this paper, under the premise of driver's revenue as the core element, combining the number of passengers waiting in line, the number of vehicles in line in the storage pool, the distance back to the city and other influencing factors, two scenarios of waiting in line to pick up passengers and returning empty to haul passengers are hypothesized, with gaining revenue over paying cost as the final measure. This problem sets up two decision scenarios as a way to build a decision model for cab driver selection. To collect the relevant data of a domestic airport and its city cabs, in order to ensure the rationality and reliable reference value of the data, Nanjing Lukou Airport is selected as the research object after a lot of data collection, and the relevant data provided by the public information of the website and the very accurate APP are used to study the flight information on July 13, 2022. For Nanjing Lukou Airport, the change of airport traffic in different time periods is relatively large, so according to the relevant data obtained, the benefits of different schemes are considered comprehensively, and the model established in Problem 1 is solved to obtain the benefits of Scheme A and B at different moments of the day, so as to give six time periods of the driver's decision scheme.

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