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Furthermore, the number of unlabelled solutions participating in model training is adaptively determined based on the objective evaluations conducted. A group of tests on DTLZ test problems with 3, 5, and 10 objective functions, combined with a practical application, are conducted to assess the effectiveness of our proposed method. Comparative experimental results versus six state-of-the-art evolutionary algorithms for expensive problems show high efficiency of SLTA-MOEA, particularly for problems with irregular Pareto fronts.<\/jats:p>","DOI":"10.1007\/s40747-024-01715-6","type":"journal-article","created":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T08:27:00Z","timestamp":1736238420000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A semi-supervised learning technique assisted multi-objective evolutionary algorithm for computationally expensive problems"],"prefix":"10.1007","volume":"11","author":[{"given":"Zijian","family":"Jiang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8011-8222","authenticated-orcid":false,"given":"Chaoli","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Xiaotong","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Hui","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Sisi","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,7]]},"reference":[{"doi-asserted-by":"publisher","unstructured":"Li G, Wang J, Li Z, Yen GG, Qi Q, Xing J (2024) Multi-objective optimization of a lower limb prosthesis for metabolically efficient walking assistance. 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