The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
New inspirations in swarm intelligence: a survey
Abstract
The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Evolutionary computation and swarm intelligence meta-heuristics are outstanding examples that nature has been an unending source of inspiration. The behaviour of bees, bacteria, glow-worms, fireflies, slime moulds, cockroaches, mosquitoes and other organisms have inspired swarm intelligence researchers to devise new optimisation algorithms. This tutorial highlights the most recent nature-based inspirations as metaphors for swarm intelligence meta-heuristics. We describe the biological behaviours from which a number of computational algorithms were developed. Also, the most recent and important applications and the main features of such meta-heuristics are reported.
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Cites
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
Cited by
Decision Making in Multiagent Systems: A Survey
Rizk, Y., Awad, M., & Tunstel, E. W. (2018) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2018.2840971 · Cited by 219
Iqbal, R., Doctor, F., More, B., Mahmud, S., & Yousuf, U. (2020) · Future Generation Computer Systems · doi:10.1016/j.future.2017.10.021 · Cited by 155
Embedded Intelligence on FPGA: Survey, Applications and Challenges
Seng, K. P., Lee, P. J., & Ang, L. M. (2021) · Electronics · doi:10.3390/electronics10080895 · Cited by 105
“In recent years, machine learning [1] and swarm intelligence [2] algorithms have demonstrated successes in many fields and solved practical problems in industry.”
BackgroundA survey on nature-inspired algorithms and its applications in the Internet of Vehicles
Sharma, S., & Kaushik, B. (2021) · International Journal of Communication Systems · doi:10.1002/dac.4895 · Cited by 14
Metadata
- Authors
- Parpinelli, R. S., & Lopes, H. S.
- Venue
- International Journal of Bio-Inspired Computation
- Publisher
- Inderscience Publishers
- Published
- 2011
- Volume
- 3
- Issue
- 1
- Pages
- 1
- ISSN
- 1758-0366 (ISSN-L)
- 1758-0374
- OpenAlex
- W2127864991
- Cited by
- 402
- References
- 1
- FWCI
- 29.86
- Type
- journal article
- Language
- en
- Open access
- closed
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- Parpinelli, R. S., & Lopes, H. S. (2011). New inspirations in swarm intelligence: a survey. International Journal of Bio-Inspired Computation. https://doi.org/10.1504/ijbic.2011.038700
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