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The presented algorithm is a variant of adaptive differential evolution (DE) algorithms, and is called emulation-based adaptive DE or EBADE. The primary aim of EBADE\u00a0is to emulate the principle of sample-efficient optimization, such as that in SAEAs, by adaptively tuning the DE parameter configurations. Specifically, similar to Expected Improvement-based sampling, EBADE\u00a0identifies parameter configurations that may produce expected-to-improve solutions, without using function evaluations. Further, EBADE\u00a0incepts a multi-population mechanism and assigns a parameter configuration to each subpopulation to estimate the effectiveness of parameter configurations with multiple samples carefully. This subpopulation-based adaptation can help improve the selection accuracy of promising parameter configurations, even when using an expected-to-improve indicator with high uncertainty, by validating with respect to multiple samples. The experimental results demonstrate that EBADE\u00a0outperforms modern adaptive DEs and is highly competitive compared to SAEAs with a much shorter runtime.<\/jats:p>","DOI":"10.1007\/s40747-023-01340-9","type":"journal-article","created":{"date-parts":[[2024,2,15]],"date-time":"2024-02-15T02:02:08Z","timestamp":1707962528000},"page":"3633-3656","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Emulation-based adaptive differential evolution: fast and auto-tunable approach for moderately expensive optimization problems"],"prefix":"10.1007","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2610-9276","authenticated-orcid":false,"given":"Kei","family":"Nishihara","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3428-7890","authenticated-orcid":false,"given":"Masaya","family":"Nakata","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,15]]},"reference":[{"issue":"32","key":"1340_CR1","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1111\/exsy.12105","volume":"4","author":"S Baskar","year":"2015","unstructured":"Baskar S, Miruna JAS (2015) Surrogate assisted-hybrid differential evolution algorithm using diversity control. 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