{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/45287"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/45287","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"A comparison of discrete and flow-based models for air traffic flow management","abstract":"The steady increase of congestion in air traffic networks has resulted in significant economic losses and potential safety issues in the air transportation. A potential way to reduce congestion is to adopt efficient air traffic management policies, such as, optimally scheduling and routing air traffic throughout the network. In recent years, several models have been proposed to predict and manage air traffic. This thesis focuses on the comparison of two such approaches to air traffic flow management: (i) a discrete Mixed Integer Program model, and (ii) a continuous flow-based model. The continuous model is applied in a multi-commodity setting to take into account the origins and destinations of the aircraft. Sequential quadratic programming is used to optimize the continuous model. A comparison of the performance of the two models based on a set of large scale test cases is provided. Preliminary results suggest that the linear programming relaxation of the discrete model provides results similar to the continuous flow-based model for high volumes of air traffic.","abstract_html":"The steady increase of congestion in air traffic networks has resulted in significant economic losses and potential safety issues in the air transportation. A potential way to reduce congestion is to adopt efficient air traffic management policies, such as, optimally scheduling and routing air traffic throughout the network. In recent years, several models have been proposed to predict and manage air traffic. This thesis focuses on the comparison of two such approaches to air traffic flow management: (i) a discrete Mixed Integer Program model, and (ii) a continuous flow-based model. The continuous model is applied in a multi-commodity setting to take into account the origins and destinations of the aircraft. Sequential quadratic programming is used to optimize the continuous model. A comparison of the performance of the two models based on a set of large scale test cases is provided. Preliminary results suggest that the linear programming relaxation of the discrete model provides results similar to the continuous flow-based model for high volumes of air traffic.","abstract_has_math":false,"creators":["Phu, Thi Vu"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Computation for Design and Optimization Program.","school":null,"contributors":[],"advisors":["Hamsa Balakrishnan."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:21:44Z","subjects":["Computation for Design and Optimization Program."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/45287","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hamsa Balakrishnan."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Computation for Design and Optimization Program."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/45287"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2008.","Includes bibliographical references (leaves 73-74)."]},{"key":"dc:description.abstract","label":"Abstract","values":["The steady increase of congestion in air traffic networks has resulted in significant economic losses and potential safety issues in the air transportation. A potential way to reduce congestion is to adopt efficient air traffic management policies, such as, optimally scheduling and routing air traffic throughout the network. In recent years, several models have been proposed to predict and manage air traffic. This thesis focuses on the comparison of two such approaches to air traffic flow management: (i) a discrete Mixed Integer Program model, and (ii) a continuous flow-based model. The continuous model is applied in a multi-commodity setting to take into account the origins and destinations of the aircraft. Sequential quadratic programming is used to optimize the continuous model. A comparison of the performance of the two models based on a set of large scale test cases is provided. Preliminary results suggest that the linear programming relaxation of the discrete model provides results similar to the continuous flow-based model for high volumes of air traffic."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["A comparison of discrete and flow-based models for air traffic flow management"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hamsa Balakrishnan."],"dc:contributor.department":["Massachusetts Institute of Technology. Computation for Design and Optimization Program."],"dc:contributor.other":["Massachusetts Institute of Technology. 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The continuous model is applied in a multi-commodity setting to take into account the origins and destinations of the aircraft. Sequential quadratic programming is used to optimize the continuous model. A comparison of the performance of the two models based on a set of large scale test cases is provided. Preliminary results suggest that the linear programming relaxation of the discrete model provides results similar to the continuous flow-based model for high volumes of air traffic."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/45287"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 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