{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/124346"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/124346","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Disaster relief vehicle routing with volunteer coverage","abstract":"In disaster relief operations, modelers typically adopt a pessimistic approach, where we optimize for the worst-case scenario. In reality, there is a chance for human compassion and support which we can incorporate in the operations: specifically, we often see volunteers who are willing to offer their help and services. In this work, we present a series of vehicle routing problems exploiting this notion of volunteers who are able to optionally provide aid to surrounding areas. We incorporate human volunteers into our problems and determine the optimal routing scheme within a network to minimize time and cost while meeting the demands of the locations. We develop a novel model based on the Miller-Tucker-Zemlin constraints, which introduces the concept of optional demands for the benefit of supporting the aid effort in an area. We reintroduce fundamental problems in vehicle routing now with a more realistic (and optimistic) component. We present computational results showcasing how volunteers may dramatically reduce the response times of the affected areas. We also present a sensitivity analysis over varying levels of volunteer availability, ability to reach farther areas (volunteer radius), and robustness of transportation infrastructure.","abstract_html":"In disaster relief operations, modelers typically adopt a pessimistic approach, where we optimize for the worst-case scenario. In reality, there is a chance for human compassion and support which we can incorporate in the operations: specifically, we often see volunteers who are willing to offer their help and services. In this work, we present a series of vehicle routing problems exploiting this notion of volunteers who are able to optionally provide aid to surrounding areas. We incorporate human volunteers into our problems and determine the optimal routing scheme within a network to minimize time and cost while meeting the demands of the locations. We develop a novel model based on the Miller-Tucker-Zemlin constraints, which introduces the concept of optional demands for the benefit of supporting the aid effort in an area. We reintroduce fundamental problems in vehicle routing now with a more realistic (and optimistic) component. We present computational results showcasing how volunteers may dramatically reduce the response times of the affected areas. We also present a sensitivity analysis over varying levels of volunteer availability, ability to reach farther areas (volunteer radius), and robustness of transportation infrastructure.","abstract_has_math":false,"creators":["Hoevener, Thomas"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Industrial Engineering","degree_department":null,"school":null,"contributors":["Vogiatzis, Chrysafis"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-04-30","date_published":"2024-04-30","updated_at":"2026-07-22T22:25:00Z","subjects":["Disaster Relief Operations","Vehicle Routing Problem","Volunteers"],"languages":["eng","en"],"rights":["Copyright 2024 Thomas Hoevener"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/124346","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Vogiatzis, Chrysafis"]},{"key":"dc:creator","label":"Author","values":["Hoevener, Thomas"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-04-30","2024-05"]},{"key":"dc:type","label":"Dc Type","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial Engineering"]},{"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":["Disaster Relief Operations","Vehicle Routing Problem","Volunteers"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng","en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Thomas Hoevener"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/124346"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In disaster relief operations, modelers typically adopt a pessimistic approach, where we optimize for the worst-case scenario. In reality, there is a chance for human compassion and support which we can incorporate in the operations: specifically, we often see volunteers who are willing to offer their help and services. In this work, we present a series of vehicle routing problems exploiting this notion of volunteers who are able to optionally provide aid to surrounding areas. We incorporate human volunteers into our problems and determine the optimal routing scheme within a network to minimize time and cost while meeting the demands of the locations. We develop a novel model based on the Miller-Tucker-Zemlin constraints, which introduces the concept of optional demands for the benefit of supporting the aid effort in an area. We reintroduce fundamental problems in vehicle routing now with a more realistic (and optimistic) component. We present computational results showcasing how volunteers may dramatically reduce the response times of the affected areas. We also present a sensitivity analysis over varying levels of volunteer availability, ability to reach farther areas (volunteer radius), and robustness of transportation infrastructure.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","The student, Thomas Hoevener, accepted the attached license on 2024-04-19 at 12:30.","The student, Thomas Hoevener, submitted this Thesis for approval on 2024-04-19 at 13:33.","This Thesis was approved for publication on 2024-04-30 at 16:42.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20501 on 2024-09-16 at 00:35:30"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Disaster relief vehicle routing with volunteer coverage"]}]}],"canonical_facts":{"dc:contributor":["Vogiatzis, Chrysafis"],"dc:creator":["Hoevener, Thomas"],"dc:date":["2024-04-30","2024-05"],"dc:description":["In disaster relief operations, modelers typically adopt a pessimistic approach, where we optimize for the worst-case scenario. In reality, there is a chance for human compassion and support which we can incorporate in the operations: specifically, we often see volunteers who are willing to offer their help and services. In this work, we present a series of vehicle routing problems exploiting this notion of volunteers who are able to optionally provide aid to surrounding areas. We incorporate human volunteers into our problems and determine the optimal routing scheme within a network to minimize time and cost while meeting the demands of the locations. We develop a novel model based on the Miller-Tucker-Zemlin constraints, which introduces the concept of optional demands for the benefit of supporting the aid effort in an area. We reintroduce fundamental problems in vehicle routing now with a more realistic (and optimistic) component. We present computational results showcasing how volunteers may dramatically reduce the response times of the affected areas. We also present a sensitivity analysis over varying levels of volunteer availability, ability to reach farther areas (volunteer radius), and robustness of transportation infrastructure.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","The student, Thomas Hoevener, accepted the attached license on 2024-04-19 at 12:30.","The student, Thomas Hoevener, submitted this Thesis for approval on 2024-04-19 at 13:33.","This Thesis was approved for publication on 2024-04-30 at 16:42.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20501 on 2024-09-16 at 00:35:30"],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/124346"],"dc:language":["eng","en"],"dc:rights":["Copyright 2024 Thomas Hoevener"],"dc:subject":["Disaster Relief Operations","Vehicle Routing Problem","Volunteers"],"dc:title":["Disaster relief vehicle routing with volunteer coverage"],"dc:type":["Text"],"thesis:degree_discipline":["Industrial Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:00Z"}