We present a method that reduces the time it takes to complete the passenger boarding of an airplane. In particular, we describe a two-stage mixed integer programming (MIP) approach, which assigns passengers to seats on an airplane based on the number of bags they carry aboard the plane. The first stage is an MIP that assigns passengers to seats to minimize the time to complete the boarding of the plane. The second-stage MIP also determines seating assignments, while constraining the total boarding time to that determined by the stage-one MIP and maximizing weighted slack times to provide a more robust assignment. Numerical results show that this two-stage approach results in lower average boarding times than the one-stage approach, when the time it takes passengers to walk and sit in their seats is random. Experiments indicate that the magnitude of the improvement is not very sensitive to variations in the slack time weights.
This paper addresses the airplane passengers’ seat assignment problem while practicing social distancing among passengers. We proposed a mixed integer programming model to assign passengers to seats on an airplane in a manner that will respect two types of social distancing. One type of social distancing refers to passengers being seated far enough away from each other. The metric for this type of social distancing is how many passengers are seated so close to each other as to increase the risk of infection. The other type of social distancing refers to the distance between seat assignments and the aisle. That distance influences the health risk involved in passengers and crew members walking down the aisle. Corresponding metrics for both health risks are included in the objective function. To conduct simulation experiments, we define different scenarios distinguishing between the relative level of significance of each type of social distancing. The results suggest the seating assignments that best serve the intention of the scenarios. We also reformulate the initial model to determine seat assignments that maximize the number of passengers boarding an airplane while practicing social distancing among passengers. In the last part of this study, we compare the proposed scenarios with the recommended middle-seat blocking policy presently used by some airlines to keep social distancing among passengers. The results show that the proposed scenarios can provide social distancing among seated passengers similar to the middle-seat blocking policy, while reducing the number of passengers seated close to the aisle of an airplane.
Research related to creating new and improved airplane boarding methods has seen continuous advancement, in recent years, while most of the airline companies have remained committed to the traditional boarding methods. Among the most-used boarding methods, around the world, are back-to-front and random boarding with and without assigned seats. While the other boarding methods used in practice possess strict rules for passengers’ behavior, random without assigned seats is dependent on the passengers own way of choosing the “best” seats. The aim of this paper is to meticulously model the passengers’ behavior, especially, in random boarding without assigned seats and to test its efficiency in terms of boarding time and interferences, in comparison with the other commonly-adopted methods (random boarding with assigned seats, window-middle-aisle (WilMA), back-to-front, reverse pyramid, etc.). One of the main challenges in our endeavor was the identification of the real human passengers’ way of reasoning, when selecting their seats, and creating a model in which the agents possess preferences and make decisions, as close to those decisions made by the human passengers, as possible. We model their choices based on completed questionnaires from three hundred and eighty-seven human subjects. This paper describes the resulting agent-based model and results from the simulations.
This paper proposes a method for reducing the time to complete the boarding of a two-door airplane when its passengers are transported from the airport terminal to the airplane using two apron buses. In contrast to other methods that assign passengers to apron buses, our method considers groups of passengers traveling together (e.g. families). In particular, we propose a mixed integer programming (MIP) model that assigns each group of passengers (including each single-passenger group) to one of the two apron buses based on their seating assignments. We assume that all seats on the apron buses and the two-door airplane are occupied. We conduct stochastic simulation experiments with the proposed MIP-based method and with a baseline method that assigns groups of passengers with seats furthest from one of the airplane doors to the first apron bus and assigns remaining groups to the second apron bus. Numerical results indicate that the proposed MIP-based method reduces the boarding time by up to 27.31% when compared with the baseline approach. INDEX TERMS Airplane boarding, group boarding, apron buses, agent-based modeling, two-door boarding, mixed integer programming.
This paper investigates the time to complete the boarding of a partially occupied two-door airplane when its passengers are transported from the airport terminal to the airplane using two apron buses. We propose a greedy method that assigns each passenger to a particular apron bus based on the passengers’ airplane seat assignments. This greedy approach exploits the airplane’s symmetry by providing essentially the same method for those boarding through the front door of the airplane as those boarding through the rear door of the airplane. The symmetrical properties of window, middle, and aisle seats of each row/side are considered in the proposed method as well. Computer simulation results indicate that, when using the greedy method, the boarding time can be reduced by up to 8.33% compared to the boarding time resulting from the best known practices in the literature, and with up to a 43.72% improvement in boarding time when compared to the boarding method commonly used in many airports. Furthermore, experimental results confirm our hypothesis that when the capacity of the apron buses exceeds the number of passengers to be transported to the airplane, the most time-efficient results of the proposed greedy method occur when an equal number of passengers are assigned to each of the two apron buses.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.