The number of passengers carried by commercial aircraft has increased dramatically over the past 50 years, closely in-step with advances in aircraft design. This makes unloading and loading an aircraft, called turn-around time, critical to the success of the airport, the aircraft and the airlines. A number of mathematical algorithms have been developed over the years that purport to determine the most efficient boarding strategy for passengers by decreasing turn time. This thesis evaluated the boarding strategies most often used by the airlines and algorithms used to predict boarding efficiency. The models used were obtained from the literature and from personal communication with the authors. The strategy and the model associated with the greatest predicted reduction in turn-around time, and the amount of time to deplane and enplane commercial airliners was determined. The Kruskal-Wallis one way analysis of variance test was used to determine that the Random boarding strategy had the greatest boarding rate and the rotating zone strategy had the slowest. It was also determined that one of the models, the Ferarri and Nagel sensitivity analysis algorithm, was consistently predictive of the empirical observations of boarding strategies.
","abstract_html":"<p>The number of passengers carried by commercial aircraft has increased dramatically over the past 50 years, closely in-step with advances in aircraft design. This makes unloading and loading an aircraft, called turn-around time, critical to the success of the airport, the aircraft and the airlines. A number of mathematical algorithms have been developed over the years that purport to determine the most efficient boarding strategy for passengers by decreasing turn time. This thesis evaluated the boarding strategies most often used by the airlines and algorithms used to predict boarding efficiency. The models used were obtained from the literature and from personal communication with the authors. The strategy and the model associated with the greatest predicted reduction in turn-around time, and the amount of time to deplane and enplane commercial airliners was determined. The Kruskal-Wallis one way analysis of variance test was used to determine that the Random boarding strategy had the greatest boarding rate and the rotating zone strategy had the slowest. It was also determined that one of the models, the Ferarri and Nagel sensitivity analysis algorithm, was consistently predictive of the empirical observations of boarding strategies.</p>","abstract_has_math":false,"creators":["Giraldo, Dalila"],"institution":null,"degree_name":"Master of Science in Human Factors & Systems","degree_level":"Thesis - Open Access","degree_discipline":"Human Factors and Systems","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-10-01T07:00:00Z","date_published":"2009-10-01T07:00:00Z","updated_at":"2026-07-27T19:26:08Z","subjects":["algorithms","commercial airlines","boarding","Aviation","Management and Operations"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/73","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Giraldo, Dalila"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Human Factors and Systems"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Human Factors & Systems"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["algorithms","commercial airlines","boarding","Aviation","Management and Operations"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/73"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The number of passengers carried by commercial aircraft has increased dramatically over the past 50 years, closely in-step with advances in aircraft design. This makes unloading and loading an aircraft, called turn-around time, critical to the success of the airport, the aircraft and the airlines. A number of mathematical algorithms have been developed over the years that purport to determine the most efficient boarding strategy for passengers by decreasing turn time. This thesis evaluated the boarding strategies most often used by the airlines and algorithms used to predict boarding efficiency. The models used were obtained from the literature and from personal communication with the authors. The strategy and the model associated with the greatest predicted reduction in turn-around time, and the amount of time to deplane and enplane commercial airliners was determined. The Kruskal-Wallis one way analysis of variance test was used to determine that the Random boarding strategy had the greatest boarding rate and the rotating zone strategy had the slowest. It was also determined that one of the models, the Ferarri and Nagel sensitivity analysis algorithm, was consistently predictive of the empirical observations of boarding strategies.
"]},{"key":"dc:title","label":"Title","values":["A Comparison of Algorithms That Estimate the Effectiveness of Commercial Airline Boarding Strategies"]}]}],"canonical_facts":{"dc:creator":["Giraldo, Dalila"],"dc:description.abstract":["The number of passengers carried by commercial aircraft has increased dramatically over the past 50 years, closely in-step with advances in aircraft design. This makes unloading and loading an aircraft, called turn-around time, critical to the success of the airport, the aircraft and the airlines. A number of mathematical algorithms have been developed over the years that purport to determine the most efficient boarding strategy for passengers by decreasing turn time. This thesis evaluated the boarding strategies most often used by the airlines and algorithms used to predict boarding efficiency. The models used were obtained from the literature and from personal communication with the authors. The strategy and the model associated with the greatest predicted reduction in turn-around time, and the amount of time to deplane and enplane commercial airliners was determined. The Kruskal-Wallis one way analysis of variance test was used to determine that the Random boarding strategy had the greatest boarding rate and the rotating zone strategy had the slowest. It was also determined that one of the models, the Ferarri and Nagel sensitivity analysis algorithm, was consistently predictive of the empirical observations of boarding strategies.
"],"dc:identifier":["https://commons.erau.edu/edt/73"],"dc:subject":["algorithms","commercial airlines","boarding","Aviation","Management and Operations"],"dc:title":["A Comparison of Algorithms That Estimate the Effectiveness of Commercial Airline Boarding Strategies"],"thesis:degree_discipline":["Human Factors and Systems"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Human Factors & Systems"]},"updated_at":"2026-07-27T19:26:08Z"}