{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/90467"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/90467","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A multi-objective sequential stochastic assignment problem for Ebola entry screening","abstract":"The 2014 Ebola outbreak in West Africa prompted a need to assess how deplaning passengers from West Africa should be managed. A 21-day quarantine requirement for deplaning passengers, based on their risk factors, was implemented at five international airports in the United States in late 2014. This thesis formulates the multi-objective sequential stochastic assignment problem (MOSSAP) to improve the process for managing such quarantine assignments. In MOSSAP, each passenger is assessed with a two-dimensional risk vector, revealed upon entering the United States, which is used to make the quarantine assignment. The objective is to maximize the expected number of passengers assigned to the correct level of monitoring (quarantine, self-monitoring), subject to quarantine capacity constraint. The weighted sum method is used to generate Pareto optimal policies for MOSSAP. Statistics available from Ebola entry screening and related public health sources are used to illustrate how such a policy would operate in practice.","abstract_html":"The 2014 Ebola outbreak in West Africa prompted a need to assess how deplaning passengers from West Africa should be managed. A 21-day quarantine requirement for deplaning passengers, based on their risk factors, was implemented at five international airports in the United States in late 2014. This thesis formulates the multi-objective sequential stochastic assignment problem (MOSSAP) to improve the process for managing such quarantine assignments. In MOSSAP, each passenger is assessed with a two-dimensional risk vector, revealed upon entering the United States, which is used to make the quarantine assignment. The objective is to maximize the expected number of passengers assigned to the correct level of monitoring (quarantine, self-monitoring), subject to quarantine capacity constraint. The weighted sum method is used to generate Pareto optimal policies for MOSSAP. Statistics available from Ebola entry screening and related public health sources are used to illustrate how such a policy would operate in practice.","abstract_has_math":false,"creators":["Yu, Ge"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Kiyavash, Negar"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-07-07T19:52:43Z","date_published":"2016-07-07T19:52:43Z","updated_at":"2026-07-22T22:26:32Z","subjects":["sequential stochastic assignment","multi-objective optimization","Ebola entry screening"],"languages":["en"],"rights":["Copyright 2016 Ge Yu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/90467","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kiyavash, Negar"]},{"key":"dc:creator","label":"Author","values":["Yu, Ge"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-07-07T19:52:43Z","2016-01-29","2016-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["sequential stochastic assignment","multi-objective optimization","Ebola entry screening"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Ge Yu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/90467"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The 2014 Ebola outbreak in West Africa prompted a need to assess how deplaning passengers from West Africa should be managed. A 21-day quarantine requirement for deplaning passengers, based on their risk factors, was implemented at five international airports in the United States in late 2014. This thesis formulates the multi-objective sequential stochastic assignment problem (MOSSAP) to improve the process for managing such quarantine assignments. In MOSSAP, each passenger is assessed with a two-dimensional risk vector, revealed upon entering the United States, which is used to make the quarantine assignment. The objective is to maximize the expected number of passengers assigned to the correct level of monitoring (quarantine, self-monitoring), subject to quarantine capacity constraint. The weighted sum method is used to generate Pareto optimal policies for MOSSAP. Statistics available from Ebola entry screening and related public health sources are used to illustrate how such a policy would operate in practice.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Ge Yu, accepted the attached license on 2016-01-28 at 15:20.","The student, Ge Yu, submitted this Thesis for approval on 2016-01-28 at 16:03.","This Thesis was approved for publication on 2016-01-29 at 17:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9053 on 2016-07-07 at 13:26:54","Made available in DSpace on 2016-07-07T19:52:43Z (GMT). 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This thesis formulates the multi-objective sequential stochastic assignment problem (MOSSAP) to improve the process for managing such quarantine assignments. In MOSSAP, each passenger is assessed with a two-dimensional risk vector, revealed upon entering the United States, which is used to make the quarantine assignment. The objective is to maximize the expected number of passengers assigned to the correct level of monitoring (quarantine, self-monitoring), subject to quarantine capacity constraint. The weighted sum method is used to generate Pareto optimal policies for MOSSAP. Statistics available from Ebola entry screening and related public health sources are used to illustrate how such a policy would operate in practice.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Ge Yu, accepted the attached license on 2016-01-28 at 15:20.","The student, Ge Yu, submitted this Thesis for approval on 2016-01-28 at 16:03.","This Thesis was approved for publication on 2016-01-29 at 17:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9053 on 2016-07-07 at 13:26:54","Made available in DSpace on 2016-07-07T19:52:43Z (GMT). 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