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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Bibliographic Details
Published in:Knowledge-based systems Vol. 163; pp. 283 - 304
Main Authors: Zhao, Weiguo, Wang, Liying, Zhang, Zhenxing
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.01.2019
Elsevier Science Ltd
Subjects:
Algorithms
Atom search optimization
Benchmark functions
Engineering
Estimating techniques
Estimation
Global optimization
Heuristic algorithm
Heuristic methods
Lennard-Jones potential
Mathematical models
Metaheuristic
Molecular dynamics
Novels
Optimization
Optimization algorithm
Optimization algorithms
Parameter estimation
Physics
World problems
Benchmark functions
Optimization algorithm
Global optimization
Metaheuristic
Parameter estimation
Heuristic algorithm
Atom search optimization
ISSN:0950-7051, 1872-7409
Online Access:Get full text
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Summary: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.
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ISSN:0950-7051
1872-7409
DOI:10.1016/j.knosys.2018.08.030