The DOI matches its Crossref record.
Firefly algorithm, stochastic test functions and design optimisation
Open accessAbstract
Modern optimisation algorithms are often metaheuristic, and they are very promising in solving NP-hard optimisation problems. In this paper, we show how to use the recently developed firefly algorithm to solve non-linear design problems. For the standard pressure vessel design optimisation, the optimal solution found by FA is far better than the best solution obtained previously in the literature. In addition, we also propose a few new test functions with either singularity or stochastic components but with known global optimality and thus they can be used to validate new optimisation algorithms. Possible topics for further research are also discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Bio inspired computing – A review of algorithms and scope of applications
Kar, A. K. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.04.018 · Cited by 578
Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model
Yaseen, Z. M., Ebtehaj, I., Bonakdari, H., Deo, R. C., Danandeh Mehr, A., Mohtar, W. H. M. W., Diop, L., El-shafie, A., & Singh, V. P. (2017) · Journal of Hydrology · doi:10.1016/j.jhydrol.2017.09.007 · Cited by 267
Computational methodologies for optimal sensor placement in structural health monitoring: A review
Tan, Y., & Zhang, L. (2020) · Structural Health Monitoring · doi:10.1177/1475921719877579 · Cited by 186
A novel efficient substitution-box design based on firefly algorithm and discrete chaotic map
Ahmed, H. A., Zolkipli, M. F., & Ahmad, M. (2019) · Neural Computing and Applications · doi:10.1007/s00521-018-3557-3 · Cited by 142
Optimal allocation, sizing of PHEV parking lots in distribution system
El-Zonkoly, A., & dos Santos Coelho, L. (2015) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2014.12.026 · Cited by 92
Nature-inspired framework for hyperspectral band selection
Nakamura, R. Y. M., Fonseca, L. M. G., Santos, J. A. D., Torres, R. D. S., Yang, X.-S., & Papa, J. P. (2014) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2013.2258351 · Cited by 70
Self-citationEvolving Long Short-Term Memory Networks
Lobo Neto, V. C., Passos, L. A., & Papa, J. P. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-50417-5_25 · Cited by 9
Metadata
- Authors
- Yang, X. S.
- Venue
- International Journal of Bio-Inspired Computation
- Publisher
- Inderscience Publishers
- Published
- 2010
- Volume
- 2
- Issue
- 2
- Pages
- 78
- ISSN
- 1758-0366 (ISSN-L)
- 1758-0374
- OpenAlex
- W2154943049
- Cited by
- 2,729
- References
- 0
- FWCI
- 56.11
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
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.