{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/131111"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/131111","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"Weekly crew scheduling for freight rail engineers : a network approach","abstract":"Freight rail engineers and conductors have long faced unpredictable and inflexible work schedules, leading to on-the-job fatigue, compromised safety and poor work-life balance. This paper aims to design robust weekly schedules for these crew members to alleviate the pressures associated with irregular and unpredictable work hours. The scheduling problem is formulated as a multi-commodity network flow problem on a directed time-space graph. Both the two-city and three-city cases are addressed. To account for the variability in trip times, a range of scenarios is defined in which demand is increased by up to 20% to build slack into the schedules. The results are validated using Monte Carlo simulation where 100 random weekly instances are generated for each scenarios and key performance metrics assessed. Major findings show that (i) optimal weekly schedules can be constructed in minutes for engineers in crew districts with two cities, and in several hours for engineers in crew districts with three cities, (ii) different percentages of demand increase significantly affect the degree of robustness, and (iii) forming crew districts with three cities rather than two gives better results in terms of required number of engineer and trip coverage rates.","abstract_html":"Freight rail engineers and conductors have long faced unpredictable and inflexible work schedules, leading to on-the-job fatigue, compromised safety and poor work-life balance. This paper aims to design robust weekly schedules for these crew members to alleviate the pressures associated with irregular and unpredictable work hours. The scheduling problem is formulated as a multi-commodity network flow problem on a directed time-space graph. Both the two-city and three-city cases are addressed. To account for the variability in trip times, a range of scenarios is defined in which demand is increased by up to 20% to build slack into the schedules. The results are validated using Monte Carlo simulation where 100 random weekly instances are generated for each scenarios and key performance metrics assessed. Major findings show that (i) optimal weekly schedules can be constructed in minutes for engineers in crew districts with two cities, and in several hours for engineers in crew districts with three cities, (ii) different percentages of demand increase significantly affect the degree of robustness, and (iii) forming crew districts with three cities rather than two gives better results in terms of required number of engineer and trip coverage rates.","abstract_has_math":false,"creators":["Lyu, Jinhua"],"institution":"The University of Texas at Austin","degree_name":"Master of Science","degree_level":"Masters","degree_discipline":"Operations Research and Industrial Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Bard, Jonathan F."],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-24T05:01:02Z","subjects":["Robust schedules","Freight rail crew scheduling","Monte Carlo simulation","Network model","Random travel times"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://doi.org/10.26153/tsw/58457"],"render_values":[{"text":"https://doi.org/10.26153/tsw/58457","href":"https://doi.org/10.26153/tsw/58457","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/2152/131111","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Bard, Jonathan F."]},{"key":"dc:creator","label":"Author","values":["Lyu, Jinhua"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-02-11T01:05:13Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-02-11T01:05:13Z"]},{"key":"dc:date.issued","label":"Date","values":["2024-05"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Operations Research and Industrial Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Texas at Austin"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Robust schedules","Freight rail crew scheduling","Monte Carlo simulation","Network model","Random travel times"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2152/131111","https://doi.org/10.26153/tsw/58457"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Freight rail engineers and conductors have long faced unpredictable and inflexible work schedules, leading to on-the-job fatigue, compromised safety and poor work-life balance. This paper aims to design robust weekly schedules for these crew members to alleviate the pressures associated with irregular and unpredictable work hours. The scheduling problem is formulated as a multi-commodity network flow problem on a directed time-space graph. Both the two-city and three-city cases are addressed. To account for the variability in trip times, a range of scenarios is defined in which demand is increased by up to 20% to build slack into the schedules. The results are validated using Monte Carlo simulation where 100 random weekly instances are generated for each scenarios and key performance metrics assessed. Major findings show that (i) optimal weekly schedules can be constructed in minutes for engineers in crew districts with two cities, and in several hours for engineers in crew districts with three cities, (ii) different percentages of demand increase significantly affect the degree of robustness, and (iii) forming crew districts with three cities rather than two gives better results in terms of required number of engineer and trip coverage rates."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Weekly crew scheduling for freight rail engineers : a network approach"]}]}],"canonical_facts":{"dc:contributor.advisor":["Bard, Jonathan F."],"dc:creator":["Lyu, Jinhua"],"dc:date.accessioned":["2025-02-11T01:05:13Z"],"dc:date.available":["2025-02-11T01:05:13Z"],"dc:date.issued":["2024-05"],"dc:description.abstract":["Freight rail engineers and conductors have long faced unpredictable and inflexible work schedules, leading to on-the-job fatigue, compromised safety and poor work-life balance. This paper aims to design robust weekly schedules for these crew members to alleviate the pressures associated with irregular and unpredictable work hours. The scheduling problem is formulated as a multi-commodity network flow problem on a directed time-space graph. Both the two-city and three-city cases are addressed. To account for the variability in trip times, a range of scenarios is defined in which demand is increased by up to 20% to build slack into the schedules. The results are validated using Monte Carlo simulation where 100 random weekly instances are generated for each scenarios and key performance metrics assessed. Major findings show that (i) optimal weekly schedules can be constructed in minutes for engineers in crew districts with two cities, and in several hours for engineers in crew districts with three cities, (ii) different percentages of demand increase significantly affect the degree of robustness, and (iii) forming crew districts with three cities rather than two gives better results in terms of required number of engineer and trip coverage rates."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/2152/131111","https://doi.org/10.26153/tsw/58457"],"dc:language.iso":["English"],"dc:subject":["Robust schedules","Freight rail crew scheduling","Monte Carlo simulation","Network model","Random travel times"],"dc:title":["Weekly crew scheduling for freight rail engineers : a network approach"],"dc:type":["Thesis"],"thesis:degree_discipline":["Operations Research and Industrial Engineering"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["The University of Texas at Austin"]},"updated_at":"2026-07-24T05:01:02Z"}