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Based on the prediction results, promising positive-transferred individuals are selected to transfer knowledge, which can effectively improve the performance of the algorithm. Finally, CEC2017 MFO benchmark problems, WCCI20-MTSO and WCCI20-MaTSO benchmark problems are used to verify the performance of the proposed algorithm EMT-ADT. Experimental results demonstrate the competiveness of EMT-ADT compared with some state-of-the-art algorithms.<\/jats:p>","DOI":"10.1007\/s40747-023-01105-4","type":"journal-article","created":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T02:01:43Z","timestamp":1685325703000},"page":"6697-6728","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Multifactorial evolutionary algorithm with adaptive transfer strategy based on decision tree"],"prefix":"10.1007","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4336-5582","authenticated-orcid":false,"given":"Wei","family":"Li","sequence":"first","affiliation":[]},{"given":"Xinyu","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,29]]},"reference":[{"key":"1105_CR1","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1109\/TEVC.2015.2458037","volume":"20","author":"A Gupta","year":"2016","unstructured":"Gupta A, Ong YS, Feng L (2016) Multifactorial evolution: toward evolutionary multitasking. 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