{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/99279"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/99279","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Mixed integer linear programming approach for solving assembly scheduling problems","abstract":"In this research, the problem of scheduling operations in manufacturing facilities with multiple machines that produce complex multi-level assemblies is considered. The problem is modeled with precedence relationships between operations. It has been formulated as a Mixed Integer Linear Program and is modeled as a flow-like problem. The objective of the problem is to reduce the total makespan (cumulative lead time) of production of final product. In addition to that, move sizes and batch sizes of operations are taken into consideration to see their impact on total makespan. Predetermined move size is used which facilitates batch overlapping, which in turn helps reduce the makespan. Column generation method has been used to solve the problem. Subproblem generates solution sets and the master problem selects from the set of generated solutions by the subproblem. Randomly generated problems with up to 100 assembly operations, 100 batch size, and 20 workcenters are used to test the formulations. Results show that makespan increases with increase in move size. This shows that batch overlapping increases the effectiveness of a schedule.","abstract_html":"In this research, the problem of scheduling operations in manufacturing facilities with multiple machines that produce complex multi-level assemblies is considered. The problem is modeled with precedence relationships between operations. It has been formulated as a Mixed Integer Linear Program and is modeled as a flow-like problem. The objective of the problem is to reduce the total makespan (cumulative lead time) of production of final product. In addition to that, move sizes and batch sizes of operations are taken into consideration to see their impact on total makespan. Predetermined move size is used which facilitates batch overlapping, which in turn helps reduce the makespan. Column generation method has been used to solve the problem. Subproblem generates solution sets and the master problem selects from the set of generated solutions by the subproblem. Randomly generated problems with up to 100 assembly operations, 100 batch size, and 20 workcenters are used to test the formulations. Results show that makespan increases with increase in move size. This shows that batch overlapping increases the effectiveness of a schedule.","abstract_has_math":false,"creators":["Ganesan, Sharathram"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Industrial Engineering","degree_department":null,"school":null,"contributors":["Nagi, Rakesh"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-03-13T15:44:36Z","date_published":"2018-03-13T15:44:36Z","updated_at":"2026-07-22T22:24:37Z","subjects":["Scheduling","Mixed Integer Linear Program (MILP)","CPLEX","Batch overlapping"],"languages":["en"],"rights":["Copyright 2017 Sharathram Ganesan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/99279","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Nagi, Rakesh"]},{"key":"dc:creator","label":"Author","values":["Ganesan, Sharathram"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-03-13T15:44:36Z","2017-09-01","2017-12"]},{"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":["Scheduling","Mixed Integer Linear Program (MILP)","CPLEX","Batch overlapping"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2017 Sharathram Ganesan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/99279"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In this research, the problem of scheduling operations in manufacturing facilities with multiple machines that produce complex multi-level assemblies is considered. The problem is modeled with precedence relationships between operations. It has been formulated as a Mixed Integer Linear Program and is modeled as a flow-like problem. The objective of the problem is to reduce the total makespan (cumulative lead time) of production of final product. In addition to that, move sizes and batch sizes of operations are taken into consideration to see their impact on total makespan. Predetermined move size is used which facilitates batch overlapping, which in turn helps reduce the makespan. Column generation method has been used to solve the problem. Subproblem generates solution sets and the master problem selects from the set of generated solutions by the subproblem. Randomly generated problems with up to 100 assembly operations, 100 batch size, and 20 workcenters are used to test the formulations. Results show that makespan increases with increase in move size. This shows that batch overlapping increases the effectiveness of a schedule.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-03-13 without embargo terms","The student, Sharathram Ganesan, accepted the attached license on 2017-08-26 at 10:55.","The student, Sharathram Ganesan, submitted this Thesis for approval on 2017-08-26 at 11:05.","This Thesis was approved for publication on 2017-09-01 at 13:54.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11616 on 2018-03-13 at 10:02:17","Made available in DSpace on 2018-03-13T15:44:36Z (GMT). No. of bitstreams: 2 GANESAN-THESIS-2017.pdf: 625793 bytes, checksum: 09945442f29a236a3a045b8ebbf566b3 (MD5) LICENSE.txt: 4215 bytes, checksum: b179d32a348f7a392f47a382f35c3d9b (MD5) Previous issue date: 2017-09-01"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Mixed integer linear programming approach for solving assembly scheduling problems"]}]}],"canonical_facts":{"dc:contributor":["Nagi, Rakesh"],"dc:creator":["Ganesan, Sharathram"],"dc:date":["2018-03-13T15:44:36Z","2017-09-01","2017-12"],"dc:description":["In this research, the problem of scheduling operations in manufacturing facilities with multiple machines that produce complex multi-level assemblies is considered. The problem is modeled with precedence relationships between operations. It has been formulated as a Mixed Integer Linear Program and is modeled as a flow-like problem. The objective of the problem is to reduce the total makespan (cumulative lead time) of production of final product. In addition to that, move sizes and batch sizes of operations are taken into consideration to see their impact on total makespan. Predetermined move size is used which facilitates batch overlapping, which in turn helps reduce the makespan. Column generation method has been used to solve the problem. Subproblem generates solution sets and the master problem selects from the set of generated solutions by the subproblem. Randomly generated problems with up to 100 assembly operations, 100 batch size, and 20 workcenters are used to test the formulations. Results show that makespan increases with increase in move size. This shows that batch overlapping increases the effectiveness of a schedule.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-03-13 without embargo terms","The student, Sharathram Ganesan, accepted the attached license on 2017-08-26 at 10:55.","The student, Sharathram Ganesan, submitted this Thesis for approval on 2017-08-26 at 11:05.","This Thesis was approved for publication on 2017-09-01 at 13:54.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11616 on 2018-03-13 at 10:02:17","Made available in DSpace on 2018-03-13T15:44:36Z (GMT). No. of bitstreams: 2 GANESAN-THESIS-2017.pdf: 625793 bytes, checksum: 09945442f29a236a3a045b8ebbf566b3 (MD5) LICENSE.txt: 4215 bytes, checksum: b179d32a348f7a392f47a382f35c3d9b (MD5) Previous issue date: 2017-09-01"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/99279"],"dc:language":["en"],"dc:rights":["Copyright 2017 Sharathram Ganesan"],"dc:subject":["Scheduling","Mixed Integer Linear Program (MILP)","CPLEX","Batch overlapping"],"dc:title":["Mixed integer linear programming approach for solving assembly scheduling problems"],"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":"2026-07-22T22:24:37Z"}