{"created":"2020-09-01T14:48:50.174666+00:00","id":4442,"links":{},"metadata":{"_buckets":{"deposit":"742bd2a6-3f98-4f03-8053-7dcf8c421a46"},"_deposit":{"id":"4442","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4442"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4442","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"An Improved Ant Colony System Based on Dynamic Candidate Set and Entropy for Traveling Salesman Problem","subitem_1551255648112":"en_US"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"The Ant Colony Optimization (ACO) is ametaheuristic algorithm used for combinatorialoptimization problems. It is a good choice formany hard combinatorial problems because it ismore efficient and produces better solutions thangreedy algorithms. However, ACO iscomputationally expensive and it can still trap inlocal optima, take a long time to compute asolution on large problem sets and prematureconvergence problem. The main idea of themodification is to limit the number of elementschoices to a sensible subset, or candidate list,which can limit the selection scope of ants ateach step and thus substantially reduce the sizeof search space and to measure the uncertaintyof the path selection and evolution by using theinformation entropy self-adaptively. Simulationstudy and performance comparison on TravelingSalesman Problem show that the improvedalgorithm can converge at global optimum witha high probability. It also shows a fasterconvergence to the solutions than the standardalgorithm."}]},"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":"2019-11-13"}],"displaytype":"preview","filename":"10003.pdf","filesize":[{"value":"774 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4442/files/10003.pdf"},"version_id":"b1180975-96fa-454c-ad2f-e5c78448ded5"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Tenth International Conference On Computer Applications (ICCA 2012)","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":"2012-02-28"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/2374"},"item_title":"An Improved Ant Colony System Based on Dynamic Candidate Set and Entropy for Traveling Salesman Problem","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-11-13","publish_status":"0","recid":"4442","relation_version_is_last":true,"title":["An Improved Ant Colony System Based on Dynamic Candidate Set and Entropy for Traveling Salesman Problem"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T00:46:23.814064+00:00"}