The DOI matches its Crossref record; 143 of the 143 references it cites were found in a registry or an index.
Quantum-inspired metaheuristic algorithms: comprehensive survey and classification
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Citations
Cites
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Simulating physics with computers
Feynman, R. P. (1982) · International Journal of Theoretical Physics · doi:10.1007/bf02650179 · Cited by 7,691
GSA: A Gravitational Search Algorithm
Rashedi, E., Nezamabadi-pour, H., & Saryazdi, S. (2009) · Information Sciences · doi:10.1016/j.ins.2009.03.004 · Cited by 7,358
Quantum theory, the Church–Turing principle and the universal quantum computer
Deutsch, D. (1985) · Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences · doi:10.1098/rspa.1985.0070 · Cited by 4,597 · cited 32×
“While performing one operation with these three Q-bits registers, the operation may be achieved concurrently (in parallel) with all 23 viable mixtures (values) from 000 to 111.”
BackgroundInfluentialFuture paths for integer programming and links to artificial intelligence
Glover, F. (1986) · Computers & Operations Research · doi:10.1016/0305-0548(86)90048-1 · Cited by 4,181
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
Han, K.-H., & Kim, J.-H. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2002.804320 · Cited by 1,585
An introduction to quantum machine learning
Schuld, M., Sinayskiy, I., & Petruccione, F. (2015) · Contemporary Physics · doi:10.1080/00107514.2014.964942 · Cited by 1,381
Dhiman, G., & Kumar, V. (2019) · Knowledge-Based Systems · doi:10.1016/j.knosys.2018.11.024 · Cited by 1,195
Hybrid metaheuristics in combinatorial optimization: A survey
Blum, C., Puchinger, J., Raidl, G. R., & Roli, A. (2011) · Applied Soft Computing · doi:10.1016/j.asoc.2011.02.032 · Cited by 787
A comprehensive survey: Whale Optimization Algorithm and its applications
Gharehchopogh, F. S., & Gholizadeh, H. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2019.03.004 · Cited by 758
Self-citation
Cited by
Abdel-Basset, M., Mohamed, R., Azeem, S. A. A., Jameel, M., & Abouhawwash, M. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110454 · Cited by 599
Scientometric Analysis of Quantum Algorithms for VANET Optimization
Pooja, & Kumar Sood, S. (2024) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2024.3428707 · Cited by 9
Metadata
- Authors
- Gharehchopogh, F. S.
- Venue
- Artificial Intelligence Review
- Published
- 2022-11-02
- Volume
- 56
- Issue
- 6
- Pages
- 5479-5543
- ISSN
- 0269-2821 (ISSN-L)
- 1573-7462
- OpenAlex
- W4308112317
- Cited by
- 253
- References
- 143
- FWCI
- 16.80
- Type
- journal article
- Language
- en
- Open access
- closed
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- Gharehchopogh, F. S. (2023). Quantum-inspired metaheuristic algorithms: comprehensive survey and classification. Artificial Intelligence Review. https://doi.org/10.1007/s10462-022-10280-8
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.
