{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/42749"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/42749","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"The application of simulated annealing to the mixed model, deterministic assembly line balancing problem","abstract":"With the trend towards greater product customization and shorter delivery time, the use of mixed model assembly lines is increasing. A line balancing approach is needed that can address the complex nature of the mixed model line and produce near optimal solutions to problems of realistic size. Due to the combinatorial nature of the line balancing problem, exact solution techniques are limited to small problems. Heuristic methods, on the other hand, are often too simplistic to find good solutions. Furthermore, many of the existing techniques cannot be expanded to handle the mixed model problem. Simulated Annealing (SA) is a search methodology which has exhibited good results when applied to combinatorial optimization problems. In fact, researchers have found that SA is able to find near-optimal solutions while its processing time increases only as a polynomial function of problem size. However, none of the applications found in the literature fully explore the technique's ability to handle a highly-constrained problem such as line balancing.","abstract_html":"With the trend towards greater product customization and shorter delivery time, the use of mixed model assembly lines is increasing. A line balancing approach is needed that can address the complex nature of the mixed model line and produce near optimal solutions to problems of realistic size. Due to the combinatorial nature of the line balancing problem, exact solution techniques are limited to small problems. Heuristic methods, on the other hand, are often too simplistic to find good solutions. Furthermore, many of the existing techniques cannot be expanded to handle the mixed model problem. Simulated Annealing (SA) is a search methodology which has exhibited good results when applied to combinatorial optimization problems. In fact, researchers have found that SA is able to find near-optimal solutions while its processing time increases only as a polynomial function of problem size. However, none of the applications found in the literature fully explore the technique's ability to handle a highly-constrained problem such as line balancing.","abstract_has_math":false,"creators":["Edwards, Sherry L."],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Industrial and Systems Engineering","degree_department":"Industrial and Systems Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Eyada, Osama K."],"committee_members":["Sarin, Subhash C.","Sumichrast, Robert T."],"year":1993,"date_issued":"1993-07-15","date_published":"1993-07-15","updated_at":"2026-07-22T22:18:49Z","subjects":[],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-05192010-020127"],"render_values":[{"text":"etd-05192010-020127","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/42749","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Eyada, Osama K."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Sarin, Subhash C.","Sumichrast, Robert T."]},{"key":"dc:contributor.department","label":"Department","values":["Industrial and Systems Engineering"]},{"key":"dc:creator","label":"Author","values":["Edwards, Sherry L."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:36:28Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:36:28Z","2010-05-19"]},{"key":"dc:date.issued","label":"Date","values":["1993-07-15"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial and Systems 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":["Virginia Polytechnic Institute and State University"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-05192010-020127"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/42749"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["With the trend towards greater product customization and shorter delivery time, the use of mixed model assembly lines is increasing. A line balancing approach is needed that can address the complex nature of the mixed model line and produce near optimal solutions to problems of realistic size. Due to the combinatorial nature of the line balancing problem, exact solution techniques are limited to small problems. Heuristic methods, on the other hand, are often too simplistic to find good solutions. Furthermore, many of the existing techniques cannot be expanded to handle the mixed model problem. Simulated Annealing (SA) is a search methodology which has exhibited good results when applied to combinatorial optimization problems. In fact, researchers have found that SA is able to find near-optimal solutions while its processing time increases only as a polynomial function of problem size. However, none of the applications found in the literature fully explore the technique's ability to handle a highly-constrained problem such as line balancing."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["BTD"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["The application of simulated annealing to the mixed model, deterministic assembly line balancing problem"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Eyada, Osama K."],"dc:contributor.committeemember":["Sarin, Subhash C.","Sumichrast, Robert T."],"dc:contributor.department":["Industrial and Systems Engineering"],"dc:creator":["Edwards, Sherry L."],"dc:date.accessioned":["2014-03-14T21:36:28Z"],"dc:date.available":["2014-03-14T21:36:28Z","2010-05-19"],"dc:date.issued":["1993-07-15"],"dc:description.abstract":["With the trend towards greater product customization and shorter delivery time, the use of mixed model assembly lines is increasing. A line balancing approach is needed that can address the complex nature of the mixed model line and produce near optimal solutions to problems of realistic size. Due to the combinatorial nature of the line balancing problem, exact solution techniques are limited to small problems. Heuristic methods, on the other hand, are often too simplistic to find good solutions. Furthermore, many of the existing techniques cannot be expanded to handle the mixed model problem. Simulated Annealing (SA) is a search methodology which has exhibited good results when applied to combinatorial optimization problems. In fact, researchers have found that SA is able to find near-optimal solutions while its processing time increases only as a polynomial function of problem size. However, none of the applications found in the literature fully explore the technique's ability to handle a highly-constrained problem such as line balancing."],"dc:description.degree":["Master of Science"],"dc:format.medium":["BTD"],"dc:format.mimetype":["application/pdf"],"dc:identifier.other":["etd-05192010-020127"],"dc:identifier.uri":["http://hdl.handle.net/10919/42749"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["The application of simulated annealing to the mixed model, deterministic assembly line balancing problem"],"dc:type":["Thesis"],"dc:type.dcmitype":["Text"],"thesis:degree_discipline":["Industrial and Systems Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:18:49Z"}