{"id":668,"date":"2025-08-30T18:00:20","date_gmt":"2025-08-30T18:00:20","guid":{"rendered":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/?page_id=668"},"modified":"2026-07-13T09:59:20","modified_gmt":"2026-07-13T09:59:20","slug":"ijett-v73i8p126","status":"publish","type":"page","link":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/ijett-v73i8p126\/","title":{"rendered":"Modified Sailfish Optimizer with Opposition Based Learning to Optimize Traveling Salesman Problem"},"content":{"rendered":"<p><span style=\"font-size: 10pt\"><strong>Title<\/strong>: Modified Sailfish Optimizer with Opposition Based Learning to Optimize Traveling Salesman Problem.<\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Published date<\/strong>: 30 August 2025<\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Publisher<\/strong>: Seventh Sense Research Group.<\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Journal<\/strong>: International Journal of Engineering Trends and Technology.<\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Volume:<\/strong> 73<br \/>\n<strong>Issue:<\/strong> 8<br \/>\n<strong>Page:<\/strong> 303-311<\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Authors<\/strong>: Prayoga Yudha Pamungkas.<\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Affiliation<\/strong>: Industrial Engineering Department, Faculty of Engineering, Bina Nusantara University, Jakarta, Indonesia.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-size: 10pt\"><strong>Abstract<\/strong><\/span><\/p>\n<p><span style=\"font-size: 10pt\">The newly proposed Modified Sailfish Optimizer (MSFO) is designed to address the issue of the Traveling Salesmen Problem (TSP) effectively. In this modification, Opposition-Based Learning (OBL) is hybridized to enhance population diversity and speed up convergence. A simplified attack power mechanism improves the exploration-exploitation balance, which helps MSFO escape local optima and find better solutions. Experimental results on benchmark TSP instances prove that MSFO outperforms among the compared algorithms. It achieves optimal solutions with zero deviation and is better than the compared algorithms. MSFO can discover the minimum possible tours that other algorithms cannot reach, and the best solution. These results confirm that the proposed modifications significantly improve the effectiveness of the original Sailfish Optimizer.<\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Keyword<\/strong><\/span><\/p>\n<p><span style=\"font-size: 10pt\">Modified Sailfish Optimizer, metaheuristics, Opposition based learning, Traveling Salesman Problem, Discrete optimization.<\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Download pdf | <a href=\"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-content\/uploads\/sites\/7\/2026\/07\/IJETT-V73I8P126-1.pdf\">IJETT-V73I8P126<\/a><\/strong><\/span><\/p>\n<p><span style=\"font-size: 10pt\"><strong>Reference<\/strong><\/span><\/p>\n<p><span style=\"font-size: 10pt\">[1] Petric\u0103 C. 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Available: http:\/\/comopt.ifi.uni-heidelberg.de\/software\/TSPLIB95\/<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-size: 10pt\"><strong>Citation<\/strong><\/span><\/p>\n<p><span style=\"font-size: 10pt\">Prayoga Yudha Pamungkas, &#8220;Modified Sailfish Optimizer with Opposition Based Learning to Optimize Traveling Salesman Problem,&#8221; International Journal of Engineering Trends and Technology (IJETT), vol. 73, no. 8, pp. 303-311, 2025. Crossref, <a href=\"https:\/\/doi.org\/10.14445\/22315381\/IJETT-V73I8P126\">https:\/\/doi.org\/10.14445\/22315381\/IJETT-V73I8P126<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Title: Modified Sailfish Optimizer with Opposition Based Learning to Optimize Traveling Salesman Problem. Published date: 30 August 2025 Publisher: Seventh Sense Research Group. Journal: International Journal of Engineering Trends and Technology. Volume: 73 Issue: 8 Page: 303-311 Authors: Prayoga Yudha Pamungkas. Affiliation: Industrial Engineering Department, Faculty of Engineering, Bina Nusantara University, Jakarta, Indonesia. &nbsp; Abstract [&hellip;]<\/p>\n","protected":false},"author":10,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-668","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-json\/wp\/v2\/pages\/668","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-json\/wp\/v2\/comments?post=668"}],"version-history":[{"count":2,"href":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-json\/wp\/v2\/pages\/668\/revisions"}],"predecessor-version":[{"id":673,"href":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-json\/wp\/v2\/pages\/668\/revisions\/673"}],"wp:attachment":[{"href":"https:\/\/binus.ac.id\/semarang\/smart-industrial-engineering\/wp-json\/wp\/v2\/media?parent=668"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}