The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Low-autocorrelation binary sequences: On improved merit factors and runtime predictions to achieve them
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“This scaling closely matches the one reported in (30).”
From Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem (2024) · cites this paper as [30]
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In the citing paper
“The best-known heuristic for general LABS is tabu search initialized with a memetic algorithm (Memetic Tabu) (23), and has a running time that scales as 1.34N (30).”
From Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem (2024) · cites this paper as [30]
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Citations
Cites
The R Project in Statistical Computing
Ripley, B. D. (2001) · MSOR Connections · doi:10.11120/msor.2001.01010023 · Cited by 2,681
Random-energy model: An exactly solvable model of disordered systems
Derrida, B. (1981) · Physical review. B, Condensed matter · doi:10.1103/physrevb.24.2613 · Cited by 1,363
Madras, N., & Slade, G. (1996) · Springer eBooks · doi:10.1007/978-1-4612-4132-4 · Cited by 698
Tufte, E. R. (2006) · Cited by 595
Gross, D. J., & Mézard, M. (1984) · Nuclear Physics B · doi:10.1016/0550-3213(84)90237-2 · Cited by 497
Landscapes and their correlation functions
Stadler, P. F. (1996) · Journal of Mathematical Chemistry · doi:10.1007/bf01165154 · Cited by 255
Some problems in real and complex analysis
Littlewood, J. E. (1968) · Medical Entomology and Zoology · Cited by 227
Sieves for low autocorrelation binary sequences
Golay, M. (1977) · IEEE Transactions on Information Theory · doi:10.1109/tit.1977.1055653 · Cited by 225
The merit factor of long low autocorrelation binary sequences (Corresp.)
Golay, M. (1982) · IEEE Transactions on Information Theory · doi:10.1109/tit.1982.1056505 · Cited by 196
Low autocorrelation binary sequences : statistical mechanics and configuration space analysis
Bernasconi, J. (1987) · Journal de physique · doi:10.1051/jphys:01987004804055900 · Cited by 188
Flagged first, then by citations
Research works printed but not linked: 3
- Beenker, 1985, Binary sequences with a maximally flat amplitude spectrum, Philips J. Res., 40, 289
- F. Brglez, J. Brest, B. Bošković, xBed: An Open Environment for Design and Experiments with Combinatorial Solvers, A preprint available from the authors.
- F. Brglez, On Stochastic Combinatorial Optimization and Markov Chains: From Walks with Self-Loops to Self-Avoiding Walks, A preprint available from the author.
Cited by
Sorted by citations
Shaydulin, R., Li, C., Chakrabarti, S., DeCross, M., Herman, D., Kumar, N., Larson, J., Lykov, D., Minssen, P., Sun, Y., et al. (2024) · Science Advances · doi:10.1126/sciadv.adm6761 · Cited by 120
“34 N (30).”
Metadata
- Authors
- Bošković, B., Brglez, F., & Brest, J.
- Affiliations
- North Carolina State University (US)
- University of Maribor (SI)
- ORCID
- Brest, Janez
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 56
- Pages
- 262-285
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W2278999310
- Cited by
- 31
- References
- 55
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 6 · 2023: 1 · 2022: 4 · 2021: 5 · 2020: 2 · 2019: 2 · 2018: 2 · 2017: 4
- FWCI
- 1.57
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Applied Soft Computing (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Slovenian Research Agency
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Physical Sciences › Mathematics › Discrete Mathematics and Combinatorics › Coding theory and cryptography
- Physical Sciences › Computer Science › Artificial Intelligence › Constraint Satisfaction and Optimization
- Keywords
- low autocorrelation binary sequences, merit factor, tabu search, self-avoiding walks
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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.
Statistics and arithmetic are recomputed, not judged.
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