The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.
Atom search optimization and its application to solve a hydrogeologic parameter estimation problem
Abstract
Abstract 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.
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Dehghani, M., Hubalovsky, S., & Trojovsky, P. (2021) · IEEE Access · doi:10.1109/access.2021.3133286 · Cited by 574
Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm
Zhao, W., Wang, L., & Zhang, Z. (2020) · Neural Computing and Applications · doi:10.1007/s00521-019-04452-x · Cited by 499
Self-citationA Novel Improved Atom Search Optimization Algorithm for Designing Power System Stabilizer
Izci, D. (2022) · Evolutionary Intelligence · doi:10.1007/s12065-021-00615-9 · Cited by 65
Metadata
- Authors
- Zhao, W., Wang, L., & Zhang, Z.
- Venue
- Knowledge-Based Systems
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 163
- Pages
- 283-304
- ISSN
- 0950-7051 (ISSN-L)
- OpenAlex
- W2889545660
- Cited by
- 699
- References
- 76
- FWCI
- 22.07
- Type
- journal article
- Language
- en
- Open access
- closed
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