Matches in SemOpenAlex for { <https://semopenalex.org/work/W3204351340> ?p ?o ?g. }
- W3204351340 endingPage "1309" @default.
- W3204351340 startingPage "1297" @default.
- W3204351340 abstract "Abstract Metaheuristics is a powerful optimization tool that is increasingly used across disciplines to tackle general purpose optimization problems. Nature‐inspired metaheuristic algorithms is a subclass of metaheuristic algorithms and have been shown to be particularly flexible and useful in solving complicated optimization problems in computer science and engineering. A common practice with metaheuristics is to hybridize it with another suitably chosen algorithm for enhanced performance. This paper reviews metaheuristic algorithms and demonstrates some of its utility in tackling pharmacometric problems. Specifically, we provide three applications using one of its most celebrated members, particle swarm optimization (PSO), and show that PSO can effectively estimate parameters in complicated nonlinear mixed‐effects models and to gain insights into statistical identifiability issues in a complex compartment model. In the third application, we demonstrate how to hybridize PSO with sparse grid, which is an often‐used technique to evaluate high dimensional integrals, to search for ‐efficient designs for estimating parameters in nonlinear mixed‐effects models with a count outcome. We also show the proposed hybrid algorithm outperforms its competitors when sparse grid is replaced by its competitor, adaptive gaussian quadrature to approximate the integral, or when PSO is replaced by three notable nature‐inspired metaheuristic algorithms." @default.
- W3204351340 created "2021-10-11" @default.
- W3204351340 creator A5024844590 @default.
- W3204351340 creator A5033093691 @default.
- W3204351340 creator A5050143476 @default.
- W3204351340 creator A5066683966 @default.
- W3204351340 creator A5078281046 @default.
- W3204351340 date "2021-10-22" @default.
- W3204351340 modified "2023-09-24" @default.
- W3204351340 title "Metaheuristics for pharmacometrics" @default.
- W3204351340 cites W1542069658 @default.
- W3204351340 cites W1555690076 @default.
- W3204351340 cites W1820051232 @default.
- W3204351340 cites W1826421496 @default.
- W3204351340 cites W1964224785 @default.
- W3204351340 cites W1968678821 @default.
- W3204351340 cites W1981928454 @default.
- W3204351340 cites W1986267161 @default.
- W3204351340 cites W1986740239 @default.
- W3204351340 cites W1993147091 @default.
- W3204351340 cites W1993284445 @default.
- W3204351340 cites W1994116065 @default.
- W3204351340 cites W1995584797 @default.
- W3204351340 cites W1997752174 @default.
- W3204351340 cites W1997857779 @default.
- W3204351340 cites W2004646768 @default.
- W3204351340 cites W2007207413 @default.
- W3204351340 cites W2012186479 @default.
- W3204351340 cites W2014509194 @default.
- W3204351340 cites W2031434350 @default.
- W3204351340 cites W2036628480 @default.
- W3204351340 cites W2038939603 @default.
- W3204351340 cites W2046133320 @default.
- W3204351340 cites W2048110904 @default.
- W3204351340 cites W2049383133 @default.
- W3204351340 cites W2049558150 @default.
- W3204351340 cites W2050947530 @default.
- W3204351340 cites W2055711652 @default.
- W3204351340 cites W2059594564 @default.
- W3204351340 cites W2063830806 @default.
- W3204351340 cites W2075088684 @default.
- W3204351340 cites W2082382318 @default.
- W3204351340 cites W2097128325 @default.
- W3204351340 cites W2104922179 @default.
- W3204351340 cites W2111393363 @default.
- W3204351340 cites W2127419446 @default.
- W3204351340 cites W2130191588 @default.
- W3204351340 cites W2159427933 @default.
- W3204351340 cites W2168289672 @default.
- W3204351340 cites W2171074980 @default.
- W3204351340 cites W2171238253 @default.
- W3204351340 cites W2230049830 @default.
- W3204351340 cites W2238904537 @default.
- W3204351340 cites W2270846035 @default.
- W3204351340 cites W2307646263 @default.
- W3204351340 cites W2312977255 @default.
- W3204351340 cites W2330107488 @default.
- W3204351340 cites W2337892520 @default.
- W3204351340 cites W2381281769 @default.
- W3204351340 cites W2407251407 @default.
- W3204351340 cites W2556336 @default.
- W3204351340 cites W2556435907 @default.
- W3204351340 cites W2604226975 @default.
- W3204351340 cites W2617674589 @default.
- W3204351340 cites W2753512919 @default.
- W3204351340 cites W2762515454 @default.
- W3204351340 cites W2778417852 @default.
- W3204351340 cites W2787501018 @default.
- W3204351340 cites W2805010611 @default.
- W3204351340 cites W2908329040 @default.
- W3204351340 cites W2922630588 @default.
- W3204351340 cites W2927015176 @default.
- W3204351340 cites W2970892738 @default.
- W3204351340 cites W3003319665 @default.
- W3204351340 cites W3037160346 @default.
- W3204351340 cites W3040588368 @default.
- W3204351340 cites W3091173904 @default.
- W3204351340 cites W3113223138 @default.
- W3204351340 cites W3204351340 @default.
- W3204351340 doi "https://doi.org/10.1002/psp4.12714" @default.
- W3204351340 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8592519" @default.
- W3204351340 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34562342" @default.
- W3204351340 hasPublicationYear "2021" @default.
- W3204351340 type Work @default.
- W3204351340 sameAs 3204351340 @default.
- W3204351340 citedByCount "3" @default.
- W3204351340 countsByYear W32043513402021 @default.
- W3204351340 countsByYear W32043513402022 @default.
- W3204351340 countsByYear W32043513402023 @default.
- W3204351340 crossrefType "journal-article" @default.
- W3204351340 hasAuthorship W3204351340A5024844590 @default.
- W3204351340 hasAuthorship W3204351340A5033093691 @default.
- W3204351340 hasAuthorship W3204351340A5050143476 @default.
- W3204351340 hasAuthorship W3204351340A5066683966 @default.
- W3204351340 hasAuthorship W3204351340A5078281046 @default.
- W3204351340 hasBestOaLocation W32043513402 @default.
- W3204351340 hasConcept C109718341 @default.
- W3204351340 hasConcept C11413529 @default.