The DOI matches its Crossref record; 71 of the 76 references it cites were found in a registry or an index.
Quantum computing for energy systems optimization: Challenges and opportunities
Open accessOverview
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Ajagekar and You [3] apply QA to three problems from energy systems, namely, facility location allocation, unit commitment, and heat exchanger networks”
From Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study (2024) · cites this paper as [3]
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
Cites
Algorithms for quantum computation: discrete logarithms and factoring
Shor, P. W. (2002) · Proceedings 35th Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.1994.365700 · Cited by 8,713
Quantum Computation and Quantum Information: 10th Anniversary Edition
Nielsen, M. A., & Chuang, I. L. (2012) · doi:10.1017/cbo9780511976667 · Cited by 8,436
Glover, F., & Laguna, M. (1997) · Cited by 5,679
Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N., & Lloyd, S. (2017) · Nature · doi:10.1038/nature23474 · Cited by 4,779
A variational eigenvalue solver on a photonic quantum processor
Peruzzo, A., McClean, J., Shadbolt, P., Yung, M.-H., Zhou, X.-Q., Love, P. J., Aspuru-Guzik, A., & O’Brien, J. L. (2014) · Nature Communications · doi:10.1038/ncomms5213 · Cited by 4,552 · cited 1×
“In the field of chemistry and optimization, a classical-quantum hybrid algorithm called Variational Quantum Eigensolver (VQE) has shown exceptional performance in terms of speed and resource utilization [31].”
BackgroundQuantum Mechanics Helps in Searching for a Needle in a Haystack
Grover, L. K. (1997) · Physical Review Letters · doi:10.1103/physrevlett.79.325 · Cited by 4,306 · cited 1×
“This is evident from the quantum algorithm proposed by Shor for factorization which is exponentially faster than any known classical algorithm [12], and Grover’s quantum search algorithm capable of searching a large database in time square root of its size [13].”
MethodQuantum Algorithm for Linear Systems of Equations
Harrow, A. W., Hassidim, A., & Lloyd, S. (2009) · Physical Review Letters · doi:10.1103/physrevlett.103.150502 · Cited by 3,325
Dowsland, K. A., & Thompson, J. M. (2012) · Springer eBooks · doi:10.1007/978-3-540-92910-9_49 · Cited by 2,470
Quantum annealing in the transverse Ising model
Kadowaki, T., & Nishimori, H. (1998) · Physical Review E · doi:10.1103/physreve.58.5355 · Cited by 2,339
Quantum computation and quantum information
Paul, T. (2007) · Mathematical Structures in Computer Science · doi:10.1017/s0960129507006317 · Cited by 2,009
A Quantum Approximate Optimization Algorithm
Farhi, E., Goldstone, J., & Gutmann, S. (2014) · arXiv · doi:10.48550/arxiv.1411.4028 · Cited by 1,789
Optimization methods applied to renewable and sustainable energy: A review
Baños, R., Manzano-Agugliaro, F. R., Montoya, F. G., Gil, C., Alcayde, A., & Gómez, J. C. L. (2011) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2010.12.008 · Cited by 1,649
Gendreau, M., & Potvin, J. (2010) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-1-4419-1665-5 · Cited by 1,648
MoS 2 transistors with 1-nanometer gate lengths
Desai, S. B., Madhvapathy, S. R., Sachid, A. B., Llinas, J. P., Wang, Q., Ahn, G. H., Pitner, G., Kim, M. J., Jeffrey Bokor, A., Hu, C. C., et al. (2016) · Science · doi:10.1126/science.aah4698 · Cited by 1,513
Assessment of sustainability indicators for renewable energy technologies
Evans, A., Strezov, V., & Evans, T. J. (2008) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2008.03.008 · Cited by 1,034
Facility location under uncertainty: a review
Snyder, L. (2006) · IIE Transactions · doi:10.1080/07408170500216480 · Cited by 1,026
Unit Commitment—A Bibliographical Survey
Padhy, N. P. (2004) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2003.821611 · Cited by 1,011
Ant Colony Optimization: Overview and Recent Advances
Dorigo, M., & Stützle, T. (2018) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-3-319-91086-4_10 · Cited by 846
Towards quantum chemistry on a quantum computer
Lanyon, B. P., Whitfield, J. D., Gillett, G. G., Goggin, M. E., Almeida, M. P., Kassal, I., Biamonte, J. D., Mohseni, M., Powell, B. J., Barbieri, M., et al. (2010) · Nature Chemistry · doi:10.1038/nchem.483 · Cited by 796
Biomass-to-bioenergy and biofuel supply chain optimization: Overview, key issues and challenges
Yue, D., You, F., & Snyder, S. W. (2013) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2013.11.016 · Cited by 768
Self-citationA survey for the quadratic assignment problem
Loiola, E. M., de Abreu, N. M. M., Boaventura-Netto, P. O., Hahn, P., & Querido, T. (2005) · European Journal of Operational Research · doi:10.1016/j.ejor.2005.09.032 · Cited by 745
Jebaraj, S., & Iniyan, S. (2004) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2004.09.004 · Cited by 688
You, F., Tao, L., Graziano, D., & Snyder, S. W. (2011) · AIChE Journal · doi:10.1002/aic.12637 · Cited by 671
Self-citationAnt Colony Optimization: Overview and Recent Advances
Dorigo, M., & Stützle, T. (2010) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-1-4419-1665-5_8 · Cited by 579
Bazmi, A. A., & Zahedi, G. (2011) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2011.05.003 · Cited by 471
Adiabatic Quantum Computation is Equivalent to Standard Quantum Computation
Aharonov, D., van Dam, W., Kempe, J., Landau, Z., Lloyd, S., & Regev, O. (2007) · SIAM Journal on Computing · doi:10.1137/s0097539705447323 · Cited by 457
Alam, T., & Kim, M.-H. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.08.060 · Cited by 428
Adiabatic Quantum Computation Is Equivalent to Standard Quantum Computation
Aharonov, D., van Dam, W., Kempe, J., Landau, Z., Lloyd, S., & Regev, O. (2008) · SIAM Review · doi:10.1137/080734479 · Cited by 395 · cited 1×
“It has also been proven that an extended form of quantum annealing is theoretically equivalent to gate (circuit) model [35].”
BackgroundOptimization of hybrid renewable energy power systems: A review
Bhandari, B., Lee, K.-T., Lee, G.-Y., Cho, Y. M., & Ahn, S. (2015) · International Journal of Precision Engineering and Manufacturing-Green Technology · doi:10.1007/s40684-015-0013-z · Cited by 389
Ceperley, D. M., & Alder, B. J. (1986) · Science · doi:10.1126/science.231.4738.555 · Cited by 374
Supply chain design and optimization: Challenges and opportunities
Garcia, D. J., & You, F. (2015) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2015.03.015 · Cited by 372
Self-citationThe impact of quantum computing on present cryptography
Mavroeidis, V., Vishi, K., D., M., & Jøsang, A. (2018) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2018.090354 · Cited by 361
Ultrafast many-body interferometry of impurities coupled to a Fermi sea
Cetina, M., Jag, M., Lous, R. S., Fritsche, I., Walraven, J. T. M., Grimm, R., Levinsen, J., Parish, M. M., Schmidt, R., Knap, M., et al. (2016) · Science · doi:10.1126/science.aaf5134 · Cited by 359
A review of heat transfer enhancement techniques in plate heat exchangers
Zhang, J., Zhu, X., Mondéjar, M. E., & Haglind, F. (2018) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2018.11.017 · Cited by 355
Handbook of Combinatorial Optimization
Du, D., & Pardalos, P. M. (1998) · Springer eBooks · doi:10.1007/978-1-4613-0303-9 · Cited by 293
The water-energy-food nexus and process systems engineering: A new focus
Garcia, D. J., & You, F. (2016) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2016.03.003 · Cited by 292
Self-citationThe synthesis of cost optimal heat exchanger networks
Gundepsen, T., & Naess, L. (1988) · Computers & Chemical Engineering · doi:10.1016/0098-1354(88)87002-9 · Cited by 291
Kammerdiner, A., Gevezes, T. P., Pasiliao, E. L., Pitsoulis, L., & Pardalos, P. M. (2013) · Springer eBooks · doi:10.1007/978-1-4419-1153-7_1152 · Cited by 284
The synthesis of cost optimal heat exchanger networks
Gundersen, T., & Naess, L. (1990) · Heat Recovery Systems and CHP · doi:10.1016/0890-4332(90)90084-w · Cited by 250
Reeves, C. R. (1993) · Cited by 231
Abujarad, S., Mustafa, M. W., & Jamian, J. J. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.11.246 · Cited by 224
The Quadratic Assignment Problem
Burkard, R. E., Çela, E., Pardalos, P. M., & Pitsoulis, L. (1998) · Springer eBooks · doi:10.1007/978-1-4613-0303-9_27 · Cited by 211
Tang, R., Li, X., & Lai, J. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.06.092 · Cited by 159
Computational complexity of heat exchanger network synthesis
Furman, K. C., & Sahinidis, N. V. (2001) · Computers & Chemical Engineering · doi:10.1016/s0098-1354(01)00681-0 · Cited by 151
Ning, C., & You, F. (2019) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2019.2891057 · Cited by 149
Self-citationHUB FACILITY LOCATION WITH FIXED COSTS
O’Kelly, M. E. (1992) · Papers of the Regional Science Association · doi:10.1111/j.1435-5597.1992.tb01848.x · Cited by 148
Strategic planning, design, and development of the shale gas supply chain network
Cafaro, D. C., & Grossmann, I. E. (2014) · AIChE Journal · doi:10.1002/aic.14405 · Cited by 146
Guan, X., Zhai, Q., & Papalexopoulos, A. D. (2004) · IEEE Power Engineering Society General Meeting · doi:10.1109/pes.2003.1270468 · Cited by 142
Biofuel supply chain design under competitive agricultural land use and feedstock market equilibrium
Bai, Y., Ouyang, Y., & Pang, J. (2012) · Energy Economics · doi:10.1016/j.eneco.2012.01.003 · Cited by 141
Nikolaev, A. G., & Jacobson, S. H. (2010) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-1-4419-1665-5_1 · Cited by 131
Hub facility location with fixed costs
O’Kelly, M. E. (1992) · Papers of the Regional Science Association · doi:10.1007/bf01434269 · Cited by 126
A Brief Review of Methods for the Design and Synthesis Optimization of Energy Systems
Frangopoulos, C. A., von Spakovsky, M. R., & Sciubba, E. (2002) · doi:10.5541/ijot.1034000097 · Cited by 125
IBM's quantum cloud computer goes commercial
Castelvecchi, D. (2017) · Nature · doi:10.1038/nature.2017.21585 · Cited by 118
Sustainable design and synthesis of energy systems
Gong, J., & You, F. (2015) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2015.09.001 · Cited by 115
Self-citationGao, J., & You, F. (2017) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2017.01.032 · Cited by 111
Self-citationAn optimization framework for the integration of water management and shale gas supply chain design
Guerra, O. J., Calderón, A. J., Papageorgiou, L. G., Siirola, J. J., & Reklaitis, G. V. (2016) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2016.03.025 · Cited by 93
Optimal siting and sizing of wind farms
Çetinay, H., Kuipers, F. A., & GÜVEN, A. N. (2016) · Renewable Energy · doi:10.1016/j.renene.2016.08.008 · Cited by 93
A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem
Abd, G., Mahmoud, A. M., & El-Sayed, M. (2014) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2014.050101 · Cited by 90
Unit commitment in electrical power system-a literature review
Bhardwaj, A., Kamboj, V. K., Shukla, V. K., Singh, B., & Khurana, P. (2012) · IEEE International Power Engineering and Optimization Conference · doi:10.1109/peoco.2012.6230874 · Cited by 64
Review of metaheuristics applied to heat exchanger network design
Toimil, D., & Gómez, A. G. (2016) · International Transactions in Operational Research · doi:10.1111/itor.12296 · Cited by 51
A language and hardware independent approach to quantum–classical computing
McCaskey, A. J., Dumitrescu, E. F., Liakh, D., Chen, M., Feng, W., & Humble, T. S. (2018) · SoftwareX · doi:10.1016/j.softx.2018.07.007 · Cited by 46
Maintenance optimization of power systems with renewable energy sources integrated
Shayesteh, E., Yu, J., & Hilber, P. (2018) · Energy · doi:10.1016/j.energy.2018.02.066 · Cited by 40
Optimization of Process Flowsheets through Metaheuristic Techniques
Ponce‐Ortega, J. M., & Hernández-Pérez, L. G. (2018) · Springer eBooks · doi:10.1007/978-3-319-91722-1 · Cited by 37
Quantum circuit design for objective function maximization in gate-model quantum computers
Gyöngyösi, L., & Imre, S. (2019) · Quantum Information Processing · doi:10.1007/s11128-019-2326-2 · Cited by 36
A deterministic method for the unit commitment problem in power systems
Zheng, H., Jian, J., Yang, L., & Quan, R. (2015) · Computers & Operations Research · doi:10.1016/j.cor.2015.01.012 · Cited by 30
Development of an optimization based design framework for microgrid energy systems
Cao, T., Hwang, Y., & Radermacher, R. (2017) · Energy · doi:10.1016/j.energy.2017.08.120 · Cited by 30
Gao, J., & You, F. (2018) · ACS Sustainable Chemistry & Engineering · doi:10.1021/acssuschemeng.8b01983 · Cited by 29
Self-citationGokbayrak, K., & Kocaman, A. S. (2017) · Computers & Operations Research · doi:10.1016/j.cor.2017.06.013 · Cited by 24
Energy Storage Emerging Strategies for Energy Storage
Boutacoff, D. (1989) · IEEE Power Engineering Review · doi:10.1109/mper.1989.4310398 · Cited by 15
Quantum Circuit Designs for Gate-Model Quantum Computer Architectures.Preprint
Gyöngyösi, L. (2018) · arXiv (Cornell University) · Cited by 5
Metaheuristic Optimization Programs
Ponce‐Ortega, J. M., & Hernández-Pérez, L. G. (2018) · Springer eBooks · doi:10.1007/978-3-319-91722-1_3 · Cited by 1
Cited by
Sorted by citations
Ghiasi, M. I., Niknam, T., Wang, Z., Mehrandezh, M., Dehghani, M., & Ghadimi, N. (2022) · Electric Power Systems Research · doi:10.1016/j.epsr.2022.108975 · Cited by 497
Quantum computing: A taxonomy, systematic review and future directions
Gill, S. S., Kumar, A., Singh, H., Singh, M., Kaur, K., Usman, M., & Buyya, R. (2021) · Software Practice and Experience · doi:10.1002/spe.3039 · Cited by 579
“Quantum computers are expected to be more energy efficient as compared to supercomputers while doing a particular task [28].”
BackgroundArtificial Intelligence and emerging digital technologies in the energy sector
Lyu, W., & Liu, J. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.117615 · Cited by 344
Using the internet of things in smart energy systems and networks
Ahmad, T., & Zhang, D. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.102783 · Cited by 332
Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects
Massaoudi, M., Abu‐Rub, H., Refaat, S. S., Chihi, I., & Oueslati, F. S. (2021) · IEEE Access · doi:10.1109/access.2021.3071269 · Cited by 280
“QDL employs Big data to speed up the training and make the computation process more efficient [184].”
Method
Metadata
- Authors
- Ajagekar, A., & You, F.
- Affiliations
- Cornell University (US)
- Corresponding author
- You, Fengqi
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 179
- Pages
- 76-89
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W2942962312
- Cited by
- 289
- References
- 76
- Citations by year
- 2026: 40 · 2025: 68 · 2024: 64 · 2023: 37 · 2022: 34 · 2021: 26 · 2020: 16 · 2019: 4
- FWCI
- 9.23
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Energy (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- arXiv (Cornell University)
- Funders
- Cornell University's
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Information and Cryptography
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- quantum computing, energy system optimization, quantum algorithms, facility location, unit commitment, heat exchanger network synthesis, quantum computing hardware, power systems
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
