Atom search optimization and its application to solve a hydrogeologic parameter estimation problem

In recent years, various metaheuristic optimization methods have been proposed in scientific and engineering fields. In this study, a novel physics-inspired metaheuristic optimization algorithm, atom search optimization (ASO), inspired by basic molecular dynamics, is developed to address a diverse s...

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Vydáno v:Knowledge-based systems Ročník 163; s. 283 - 304
Hlavní autoři: Zhao, Weiguo, Wang, Liying, Zhang, Zhenxing
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 01.01.2019
Elsevier Science Ltd
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ISSN:0950-7051, 1872-7409
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Shrnutí:In recent years, various metaheuristic optimization methods have been proposed in scientific and engineering fields. In this study, a novel physics-inspired metaheuristic optimization algorithm, atom search optimization (ASO), inspired by basic molecular dynamics, is developed to address a diverse set of optimization problems. ASO mathematically models and mimics the atomic motion model in nature, where atoms interact through interaction forces resulting from the Lennard-Jones potential and constraint forces resulting from the bond-length potential. The proposed algorithm is simple and easy to implement. ASO is tested on a range of benchmark functions to verify its validity, qualitatively and quantitatively, and then applied to a hydrogeologic parameter estimation problem with success. The results demonstrate that ASO is superior to some classic and newly emerging algorithms in the literature and is a promising solution to real-world engineering problems. •A novel optimization algorithm called Atom Search Optimization (ASO) is proposed.•ASO is benchmarked on 37 well-known test functions.•The results on test functions show the competitiveness of ASO.•The results on hydrogeologic parameter estimation confirm the performance of ASO.
Bibliografie:ObjectType-Article-1
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ISSN:0950-7051
1872-7409
DOI:10.1016/j.knosys.2018.08.030