{"id":{"repo_id":"siu-theses","oai_identifier":"oai:opensiuc.lib.siu.edu:dissertations-2243"},"canonical_url":"https://search.dev.ndltd.org/etd/siu-theses/oai:opensiuc.lib.siu.edu:dissertations-2243","repository":{"repo_id":"siu-theses","name":"Southern Illinois University","base_url":"https://opensiuc.lib.siu.edu/do/oai/"},"display":{"title":"RESOURCE CONSTRAINT COOPERATIVE GAME WITH MONTE CARLO TREE SEARCH","abstract":"A hybrid methodology of game theory and Monte Carlo Tree Search was developed and the hybrid methodology was tested with various case studies through the nurse scheduling problem to show that it was able to form Pareto front dominance solutions, finding feasible solutions that were optimal and finding feasible partial solutions in over-constrained problems. The performance comparison was carried out with the Genetic Algorithm on the Resident Physician Scheduling problem and showed that the hybrid methodology was able to produce better quality solutions compared to the state of the art approach.","abstract_html":"A hybrid methodology of game theory and Monte Carlo Tree Search was developed and the hybrid methodology was tested with various case studies through the nurse scheduling problem to show that it was able to form Pareto front dominance solutions, finding feasible solutions that were optimal and finding feasible partial solutions in over-constrained problems. The performance comparison was carried out with the Genetic Algorithm on the Resident Physician Scheduling problem and showed that the hybrid methodology was able to produce better quality solutions compared to the state of the art approach.","abstract_has_math":false,"creators":["Cheng, Chee Chian"],"institution":null,"degree_name":"Doctor of Philosophy","degree_level":"Campus Only Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Carver, Norman"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-08-01T07:00:00Z","date_published":"2016-08-01T07:00:00Z","updated_at":"2026-07-24T04:35:00Z","subjects":["cooperative game","monte carlo tree search","nurse scheduling problem","physician scheduling problem","resource constraint"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://opensiuc.lib.siu.edu/dissertations/1239","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Carver, Norman"]},{"key":"dc:creator","label":"Author","values":["Cheng, Chee Chian"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Campus Only Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["cooperative game","monte carlo tree search","nurse scheduling problem","physician scheduling problem","resource constraint"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://opensiuc.lib.siu.edu/dissertations/1239"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A hybrid methodology of game theory and Monte Carlo Tree Search was developed and the hybrid methodology was tested with various case studies through the nurse scheduling problem to show that it was able to form Pareto front dominance solutions, finding feasible solutions that were optimal and finding feasible partial solutions in over-constrained problems. The performance comparison was carried out with the Genetic Algorithm on the Resident Physician Scheduling problem and showed that the hybrid methodology was able to produce better quality solutions compared to the state of the art approach."]},{"key":"dc:title","label":"Title","values":["RESOURCE CONSTRAINT COOPERATIVE GAME WITH MONTE CARLO TREE SEARCH"]}]}],"canonical_facts":{"dc:contributor":["Carver, Norman"],"dc:creator":["Cheng, Chee Chian"],"dc:description.abstract":["A hybrid methodology of game theory and Monte Carlo Tree Search was developed and the hybrid methodology was tested with various case studies through the nurse scheduling problem to show that it was able to form Pareto front dominance solutions, finding feasible solutions that were optimal and finding feasible partial solutions in over-constrained problems. The performance comparison was carried out with the Genetic Algorithm on the Resident Physician Scheduling problem and showed that the hybrid methodology was able to produce better quality solutions compared to the state of the art approach."],"dc:identifier":["https://opensiuc.lib.siu.edu/dissertations/1239"],"dc:subject":["cooperative game","monte carlo tree search","nurse scheduling problem","physician scheduling problem","resource constraint"],"dc:title":["RESOURCE CONSTRAINT COOPERATIVE GAME WITH MONTE CARLO TREE SEARCH"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Campus Only Dissertation"],"thesis:degree_name":["Doctor of Philosophy"]},"updated_at":"2026-07-24T04:35:00Z"}