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In this study, a novel surrogate-assisted normal search particle swarm optimization (SANSPSO) was proposed to enhance the accuracy and robustness of existing methodologies. In SANSPSO, the sampling process was considered a minimum problem with an objective function defined as the absolute value of the performance function. Initiated with a normal search paradigm and supplemented by three algorithm strategies, this approach seeks to preserve the continuity of the solution while refining the algorithm\u2019s efficacy and efficiency. To reduce computation cost, surrogate-assistance was used, in which a surrogate model substitutes the objective function in most iterations. This surrogate model evolves during the iteration process and ultimately replaces the actual performance function within Monte Carlo simulation. Finally, this study presents a comparative study with five state-of-the-art methods across four explicit problems and three engineering cases, where test data suggest that the SANSPSO methodology yields a 20% improvement in accuracy and a 30% rise in stability under different dimensional problems relative to the most efficacious of the alternate methods assessed because of the improved and more consistent prediction of limit state function. These findings substantiate the validity and robustness of the SANSPSO approach.<\/jats:p>","DOI":"10.1093\/jcde\/qwae003","type":"journal-article","created":{"date-parts":[[2024,1,16]],"date-time":"2024-01-16T00:39:39Z","timestamp":1705365579000},"page":"173-194","source":"Crossref","is-referenced-by-count":4,"title":["Efficient slope reliability analysis using a surrogate-assisted normal search particle swarm optimization algorithm"],"prefix":"10.1093","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1330-572X","authenticated-orcid":false,"given":"Yi-li","family":"Yuan","sequence":"first","affiliation":[{"name":"School of Architecture and Civil Engineering, Xi'an University of Science and Technology , Xi'an, Shaanxi 710055 , China"},{"name":"College of Civil Engineering, Xi'an University of Architecture and Technology , Xi'an, Shaanxi 710055 , 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