{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/112465"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/112465","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"A heuristic for including black box analysis tools into a geometric programming formulation","abstract":"Recently, geometric programming has been proposed as a powerful tool for enhancing aircraft conceptual design. While geometric programming has shown promise in early studies, current formulations preclude the designer from using black box analysis codes which are prolific in the aircraft design community. Previous work has shown the ability to fit data from these black box codes prior to the optimization run, however, this is often a time consuming and computationally expensive process that does not scale well to higher dimensional black boxes. Based upon existing iterative optimization methods, we propose a heuristic for including black box analysis codes in a geometric programming framework by utilizing sequential geometric programming (SGP). We demonstrate a heuristic SGP method and apply it to a solar powered aircraft using a black boxed GP compatible profile drag function. Using this heuristic algorithm, we achieve less than a 1% difference in the objective function between a direct implementation of the constraint and a black box implementation of the constraint.","abstract_html":"Recently, geometric programming has been proposed as a powerful tool for enhancing aircraft conceptual design. While geometric programming has shown promise in early studies, current formulations preclude the designer from using black box analysis codes which are prolific in the aircraft design community. Previous work has shown the ability to fit data from these black box codes prior to the optimization run, however, this is often a time consuming and computationally expensive process that does not scale well to higher dimensional black boxes. Based upon existing iterative optimization methods, we propose a heuristic for including black box analysis codes in a geometric programming framework by utilizing sequential geometric programming (SGP). We demonstrate a heuristic SGP method and apply it to a solar powered aircraft using a black boxed GP compatible profile drag function. Using this heuristic algorithm, we achieve less than a 1% difference in the objective function between a direct implementation of the constraint and a black box implementation of the constraint.","abstract_has_math":false,"creators":["Karcher, Cody Jacob"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.","school":null,"contributors":[],"advisors":["Warren W. Hoburg."],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017","date_published":"2017","updated_at":"2026-07-22T22:22:06Z","subjects":["Aeronautics and Astronautics."],"languages":["eng"],"rights":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/112465","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Warren W. Hoburg."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Aeronautics and Astronautics."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written 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/1721.1/112465"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017.","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 79-82)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Recently, geometric programming has been proposed as a powerful tool for enhancing aircraft conceptual design. While geometric programming has shown promise in early studies, current formulations preclude the designer from using black box analysis codes which are prolific in the aircraft design community. Previous work has shown the ability to fit data from these black box codes prior to the optimization run, however, this is often a time consuming and computationally expensive process that does not scale well to higher dimensional black boxes. Based upon existing iterative optimization methods, we propose a heuristic for including black box analysis codes in a geometric programming framework by utilizing sequential geometric programming (SGP). We demonstrate a heuristic SGP method and apply it to a solar powered aircraft using a black boxed GP compatible profile drag function. Using this heuristic algorithm, we achieve less than a 1% difference in the objective function between a direct implementation of the constraint and a black box implementation of the constraint."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["A heuristic for including black box analysis tools into a geometric programming formulation"]}]}],"canonical_facts":{"dc:contributor.advisor":["Warren W. Hoburg."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Aeronautics and Astronautics."],"dc:contributor.other":["Massachusetts Institute of Technology. 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Based upon existing iterative optimization methods, we propose a heuristic for including black box analysis codes in a geometric programming framework by utilizing sequential geometric programming (SGP). We demonstrate a heuristic SGP method and apply it to a solar powered aircraft using a black boxed GP compatible profile drag function. Using this heuristic algorithm, we achieve less than a 1% difference in the objective function between a direct implementation of the constraint and a black box implementation of the constraint."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/112465"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Aeronautics and Astronautics."],"dc:title":["A heuristic for including black box analysis tools into a geometric programming formulation"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:22:06Z"}