{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/43040"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/43040","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"An application of artificial intelligence methods to scheduling parallel processors","abstract":"This research investigated applying Artificial Intelligence (AI) method to develop a scheduling and sequencing system for parallel processors, subject to preference, sequencing, and buffer inventory constraints. Specifically, hierarchical planning and, constraint-directed search were used to develop prototype scheduling system for a case study problem. This research also investigated dividing the scheduling problem into sub-periods to allow parallel scheduling and efficient handling of time-dependent, constraints. The prototype system uses, problem-constraints to define sub-period boundaries, and determine which processors and jobs to include in the sub-period problems. It then solves the sub-period schedules in sequence. The prototype system was tested using operational data from the case study and compared to schedules created by the case study scheduler. The prototype system produced schedules very similar to the human scheduler, and relaxed constraints only slightly more than the scheduler in searching for solutions. The success of the prototype system demonstrated: 1) the effectiveness of hierarchical planning and constraint-directed search as methods for developing scheduling systems for parallel processors; 2) that constraint satisfaction, as opposed to solving an objective function, is a useful alternative method for modeling scheduling problems; and 3) dividing the scheduling problem into sub-period problems reduces the size of the search space- encountered in parallel scheduling while allowing fulfillment of time dependent constraints.","abstract_html":"This research investigated applying Artificial Intelligence (AI) method to develop a scheduling and sequencing system for parallel processors, subject to preference, sequencing, and buffer inventory constraints. Specifically, hierarchical planning and, constraint-directed search were used to develop prototype scheduling system for a case study problem. This research also investigated dividing the scheduling problem into sub-periods to allow parallel scheduling and efficient handling of time-dependent, constraints. The prototype system uses, problem-constraints to define sub-period boundaries, and determine which processors and jobs to include in the sub-period problems. It then solves the sub-period schedules in sequence. The prototype system was tested using operational data from the case study and compared to schedules created by the case study scheduler. The prototype system produced schedules very similar to the human scheduler, and relaxed constraints only slightly more than the scheduler in searching for solutions. The success of the prototype system demonstrated: 1) the effectiveness of hierarchical planning and constraint-directed search as methods for developing scheduling systems for parallel processors; 2) that constraint satisfaction, as opposed to solving an objective function, is a useful alternative method for modeling scheduling problems; and 3) dividing the scheduling problem into sub-period problems reduces the size of the search space- encountered in parallel scheduling while allowing fulfillment of time dependent constraints.","abstract_has_math":false,"creators":["Steffen, Mitchell S."],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Industrial Engineering and Operations Research","degree_department":"Industrial Engineering and Operations Research","school":null,"contributors":[],"advisors":[],"committee_chairs":["Greene, Timothy J."],"committee_members":["Sarin, Subhash C.","Roach, John W."],"year":1985,"date_issued":"1985-08-05","date_published":"1985-08-05","updated_at":"2026-07-22T22:19:51Z","subjects":[],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-06102012-040200"],"render_values":[{"text":"etd-06102012-040200","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/43040","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Greene, Timothy J."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Sarin, Subhash C.","Roach, John W."]},{"key":"dc:contributor.department","label":"Department","values":["Industrial Engineering and Operations Research"]},{"key":"dc:creator","label":"Author","values":["Steffen, Mitchell S."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:37:39Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:37:39Z","2012-06-10"]},{"key":"dc:date.issued","label":"Date","values":["1985-08-05"]},{"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 Engineering and Operations Research"]},{"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: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-06102012-040200"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/43040"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This research investigated applying Artificial Intelligence (AI) method to develop a scheduling and sequencing system for parallel processors, subject to preference, sequencing, and buffer inventory constraints. 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