{"created":"2020-09-01T10:02:40.679937+00:00","id":3379,"links":{},"metadata":{"_buckets":{"deposit":"82ed4082-d65d-4dd0-81d3-ac5152959976"},"_deposit":{"id":"3379","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3379"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3379","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"An Ant Colony Optimization Algorithm for Solving Traveling Salesman Problem","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Ant Colony Optimization (ACO) is a class ofheuristic search algorithms that have beensuccessfully applied to solving combinationaloptimization (CO) problems. The traveling salesmanproblem (TSP) is among the most importantcombinatorial problems. ACO has very good searchcapability for optimization problems. But it still hassome drawbacks such as stagnation behavior, longcomputational time, and premature convergenceproblem of the basic ACO algorithm on TSP. Thoseproblems will be more obvious when thecomplexities of the considered problems increase.The proposed system based on basic ACO algorithmbased on well-positioned the ants on the initiationand information entropy which is applied to tuningof the algorithm’s parameters. Then, ACO for TSPhas been improved by incorporating localoptimization heuristic. Therefore, the proposedsystem intends to reach superior searchperformance over traditional ACO algorithms do."}]},"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":"2019-07-22"}],"displaytype":"preview","filename":"psc2010paper (197).pdf","filesize":[{"value":"243 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3379/files/psc2010paper (197).pdf"},"version_id":"798f2f44-7da0-409d-b117-d6c5ee6bec86"}]},"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":"Hlaing, Zar Chi Su Su"},{"subitem_authors_fullname":"Khine, May Aye"}]}]},"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/123456789/1136"},"item_title":"An Ant Colony Optimization Algorithm for Solving Traveling Salesman Problem","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-22","publish_status":"0","recid":"3379","relation_version_is_last":true,"title":["An Ant Colony Optimization Algorithm for Solving Traveling Salesman Problem"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T08:07:52.163977+00:00"}