{"created":"2020-09-01T13:06:40.511927+00:00","id":3529,"links":{},"metadata":{"_buckets":{"deposit":"5a9709c6-26f1-41f4-8e6a-74a968d9e945"},"_deposit":{"id":"3529","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3529"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3529","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Non Linear Great Deluge Hyper Heuristic with Reinforcement Learning for Scheduling Problem","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Nowadays, scheduling problems arise in almostall areas of human activity. To handle the complexityof the real world scheduling problems, manyresearchers have been invested over the years.Currently research is being directed to raise the levelof generality. Therefore, this has led to thedevelopment of hyper heuristics system. A hyperheuristic is high level problem solving methodologythat performs a search over the space generated by aset of low level heuristics. A motivating goal of hyperheuristic research is to create automated techniquesthat applicable to a wide range of problems withdifferent characteristics. One of the hyper heuristicframeworks is based on a single point searchcontaining two main stages: heuristic selection andmove acceptance. By using exam timetablingproblem as a test bed, this paper proposes the nonlinear great deluge hyper heuristic withreinforcement learning method to intend to improvethe performance of hyper heuristic"}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value":[]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-25"}],"displaytype":"preview","filename":"psc2010paper (68).pdf","filesize":[{"value":"45 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3529/files/psc2010paper (68).pdf"},"version_id":"adf98e7e-475a-404b-bfc4-96abea57f2a2"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fifth Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Sin, Ei Shwe"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2010-12-16"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1270"},"item_title":"Non Linear Great Deluge Hyper Heuristic with Reinforcement Learning for Scheduling Problem","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-25","publish_status":"0","recid":"3529","relation_version_is_last":true,"title":["Non Linear Great Deluge Hyper Heuristic with Reinforcement Learning for Scheduling Problem"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T03:54:02.338134+00:00"}