The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
The runner-root algorithm: A metaheuristic for solving unimodal and multimodal optimization problems inspired by runners and roots of plants in nature
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In the citing paper
“In contrast, meta-heuristic optimization algorithms, owing to their broad applicability, are capable of addressing optimization demands in complex scenarios [26].”
From Research on Energy-Saving Optimization of Mushroom Growing Control Room Based on Neural Network Model Predictive Control (2025) · cites this paper as [26]
Citations
Cites
Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
No free lunch theorems for optimization
Wolpert, D. H., & Macready, W. G. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585893 · Cited by 14,237
Karaboğa, D., & Akay, B. (2007) · Journal of Global Optimization · doi:10.1007/s10898-007-9149-x · Cited by 7,819
Gonzalez, T. F. (2007) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420010749-33 · Cited by 6,655
Multivariable Feedback Control: Analysis and Design
Skogestad, S., & Postlethwaite, I. (1996) · Cited by 6,312
Derrac, J., García, S., Molina, D., & Herrera, F. (2011) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2011.02.002 · Cited by 5,562
Rao, R. V., Savsani, V. J., & Vakharia, D. P. (2011) · Computer-Aided Design · doi:10.1016/j.cad.2010.12.015 · Cited by 5,318
Dorigo, M., Birattari, M., & Stützle, T. (2006) · IEEE Computational Intelligence Magazine · doi:10.1109/mci.2006.329691 · Cited by 5,314
Cited by
Song, Y., Zheng, W., Guo, G., Wang, M., Luo, C., Chen, C., & Li, Z. (2025) · Energies · doi:10.3390/en18205550 · Cited by 3
Metadata
- Authors
- Merrikh-Bayat, F.
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2015-08
- Volume
- 33
- Pages
- 292-303
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W252392022
- Cited by
- 134
- References
- 49
- Citations by year
- 2026: 2 · 2025: 13 · 2024: 5 · 2023: 15 · 2022: 11 · 2021: 17 · 2020: 22 · 2019: 22 · 2018: 11 · 2017: 10 · 2016: 5 · 2015: 1
- FWCI
- 8.83
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Applied Soft Computing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Immune Systems Applications
- Keywords
- metaheuristic optimization, multimodal optimization, unimodal optimization, local optima avoidance, exploration and exploitation, bio-inspired algorithms
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The runner-root algorithm: A metaheuristic for solving unimodal and multimodal optimization problems inspired by runners and roots of plants in nature. https://app.cochat.ai/papers/10.1016/j.asoc.2015.04.048
- The paper
- Merrikh-Bayat, F. (2015). The runner-root algorithm: A metaheuristic for solving unimodal and multimodal optimization problems inspired by runners and roots of plants in nature. Applied Soft Computing. https://doi.org/10.1016/j.asoc.2015.04.048
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
