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Subsequently, the POX-heuristic GA is developed and its performance is evaluated using data from 10 distinct tournaments. A comparison between the outcomes obtained from the proposed method and the results generated by the LeagueLobster software demonstrates that the proposed approach achieves a higher level of efficiency, with improvements ranging from 10.87% to 335.03% over the original actual schedule. The contributions stem from the successful integration of POX, heuristic techniques, and GAs to address the issue of poorly performing genes within chromosomes, ultimately leading to more effective optimization of the chromosomes. <\/jats:p>","DOI":"10.1142\/s0219622025500221","type":"journal-article","created":{"date-parts":[[2025,2,11]],"date-time":"2025-02-11T10:59:20Z","timestamp":1739271560000},"page":"1613-1629","source":"Crossref","is-referenced-by-count":0,"title":["Smart Tournament Scheduling Using a POX-Heuristic Genetic Algorithm"],"prefix":"10.1142","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1263-9912","authenticated-orcid":false,"given":"Mu-Chun","family":"Su","sequence":"first","affiliation":[{"name":"Department of Computer Science and Information Engineering, National Central University, Jhongli, Taoyuan 320317, 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