{"id":{"repo_id":"nps","oai_identifier":"oai:calhoun.nps.edu:10945/39012"},"canonical_url":"https://search.dev.ndltd.org/etd/nps/oai:calhoun.nps.edu:10945/39012","repository":{"repo_id":"nps","name":"Naval Postgraduate School","base_url":"https://calhoun.nps.edu/server/oai/request"},"display":{"title":"Assignment problem for the U.S. Marine Corps: regional, culture, and language familiarization program","abstract":"U.S. Marine Corps recently developed the Regional, Culture, and Language Familiarization Program (RCLF), which assigns newly promoted sergeants and commissioned officers to one of the 17 regions established by the RCLF office. As of now, there is no formal process established in assigning Marines to one of the 17 regions. The assignment is done manually and oftentimes, by random allocation without a standard operating procedure. We developed two integer-programming models and a matching algorithm that utilizes top trading cycle and serial dictatorship. These models optimize the assignment based on Marines and USMC preferences. We find that the benchmark integer programing model is the best in terms of assigning most Marines within their top four choices. Regardless, satisfaction rate of any of the three models are higher than the random assignment model.","abstract_html":"U.S. Marine Corps recently developed the Regional, Culture, and Language Familiarization Program (RCLF), which assigns newly promoted sergeants and commissioned officers to one of the 17 regions established by the RCLF office. As of now, there is no formal process established in assigning Marines to one of the 17 regions. The assignment is done manually and oftentimes, by random allocation without a standard operating procedure. We developed two integer-programming models and a matching algorithm that utilizes top trading cycle and serial dictatorship. These models optimize the assignment based on Marines and USMC preferences. We find that the benchmark integer programing model is the best in terms of assigning most Marines within their top four choices. Regardless, satisfaction rate of any of the three models are higher than the random assignment model.","abstract_has_math":false,"creators":["Seipel, Petra L."],"institution":"Monterey, CA; Naval Postgraduate School","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Myung, Noah"],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-12","date_published":"2013-12","updated_at":"2026-07-27T20:24:23Z","subjects":[],"languages":[],"rights":["This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10945/39012","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Myung, Noah"]},{"key":"dc:creator","label":"Author","values":["Seipel, Petra L."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-02-18T23:39:16Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-02-18T23:39:16Z"]},{"key":"dc:date.issued","label":"Date","values":["2013-12"]},{"key":"dc:publisher","label":"Institution","values":["Monterey, CA; Naval Postgraduate School"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10945/39012"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["U.S. Marine Corps recently developed the Regional, Culture, and Language Familiarization Program (RCLF), which assigns newly promoted sergeants and commissioned officers to one of the 17 regions established by the RCLF office. As of now, there is no formal process established in assigning Marines to one of the 17 regions. The assignment is done manually and oftentimes, by random allocation without a standard operating procedure. We developed two integer-programming models and a matching algorithm that utilizes top trading cycle and serial dictatorship. These models optimize the assignment based on Marines and USMC preferences. We find that the benchmark integer programing model is the best in terms of assigning most Marines within their top four choices. Regardless, satisfaction rate of any of the three models are higher than the random assignment model."]},{"key":"dc:title","label":"Title","values":["Assignment problem for the U.S. Marine Corps: regional, culture, and language familiarization program"]}]}],"canonical_facts":{"dc:contributor.advisor":["Myung, Noah"],"dc:creator":["Seipel, Petra L."],"dc:date.accessioned":["2014-02-18T23:39:16Z"],"dc:date.available":["2014-02-18T23:39:16Z"],"dc:date.issued":["2013-12"],"dc:description.abstract":["U.S. Marine Corps recently developed the Regional, Culture, and Language Familiarization Program (RCLF), which assigns newly promoted sergeants and commissioned officers to one of the 17 regions established by the RCLF office. As of now, there is no formal process established in assigning Marines to one of the 17 regions. The assignment is done manually and oftentimes, by random allocation without a standard operating procedure. We developed two integer-programming models and a matching algorithm that utilizes top trading cycle and serial dictatorship. These models optimize the assignment based on Marines and USMC preferences. We find that the benchmark integer programing model is the best in terms of assigning most Marines within their top four choices. Regardless, satisfaction rate of any of the three models are higher than the random assignment model."],"dc:identifier.uri":["https://hdl.handle.net/10945/39012"],"dc:publisher":["Monterey, CA; Naval Postgraduate School"],"dc:rights":["This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States."],"dc:title":["Assignment problem for the U.S. Marine Corps: regional, culture, and language familiarization program"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T20:24:23Z"}