Quantum Annealing Applied to De-Conflicting Optimal Trajectories for Air Traffic Management

Diameter of the World-Wide Web

Albert, R., Jeong, H., & Barabási, A.-Ĺ. (1999) · Nature · doi:10.1038/43601 · Cited by 4,240 · see citing works

A review of conflict detection and resolution modeling methods

Kuchar, J. K., & Lh, Y. (2000) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/6979.898217 · Cited by 1,070 · see citing works

Minor-embedding in adiabatic quantum computation: I. The parameter setting problem

Choi, V. (2008) · Quantum Information Processing · doi:10.1007/s11128-008-0082-9 · Cited by 410 · see citing works

Nonserial Dynamic Programming

(1972) · Mathematics in Science and Engineering/Mathematics in science and engineering · doi:10.1016/s0076-5392(08)x6010-2 · Cited by 341 · see citing works

A practical heuristic for finding graph minorsPreprint

Cai, J. L., Macready, W. G., & Roy, A. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1406.2741 · Cited by 284 · see citing works

S-functions for graphs

Halin, R. (1976) · Journal of Geometry · doi:10.1007/bf01917434 · Cited by 265 · see citing works

On non-serial dynamic programming

Bertelè, U., & Brioschi, F. (1973) · Journal of Combinatorial Theory Series A · doi:10.1016/0097-3165(73)90016-2 · Cited by 231 · see citing works

A case study in programming a quantum annealer for hard operational planning problems

Rieffel, E. G., Venturelli, D., O’Gorman, B., Do, M. B., Prystay, E. M., & Smelyanskiy, V. (2014) · Quantum Information Processing · doi:10.1007/s11128-014-0892-x · Cited by 221 · see citing works

Complexity of Scheduling Shops with No Wait in Process

Sahni, S. K., & Cho, Y. (1979) · Mathematics of Operations Research · doi:10.1287/moor.4.4.448 · Cited by 132 · see citing works

Quantum Annealing Implementation of Job-Shop SchedulingPreprint

Venturelli, D., Marchand, D. J. J., & Rojo, G. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1506.08479 · Cited by 129 · see citing works

Efficient Cluster Algorithm for Spin Glasses in Any Space Dimension.

Zhu, Z., Ochoa, A., & Katzgraber, H. (2015) · Physical Review Letters · doi:10.1103/physrevlett.115.077201 · Cited by 126 · see citing works

Coordinating the motions of multiple robots with specified trajectories

Akella, S., & Hutchinson, S. (2003) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2002.1013428 · Cited by 112 · see citing works

Strengths and weaknesses of weak-strong cluster problems: A detailed overview of state-of-the-art classical heuristics versus quantum approaches

Mandrà, S., Zhu, Z., Wang, W., Perdomo‐Ortiz, A., & Katzgraber, H. G. (2016) · Physical Review A · doi:10.1103/physreva.94.022337 · Cited by 108 · see citing works

Improved Exact Solver for the Weighted MAX-SAT Problem

Kügel, A. (2018) · EPiC series in computing · doi:10.29007/38lm · Cited by 88 · see citing works

Best-case performance of quantum annealers on native spin-glass benchmarks: How chaos can affect success probabilities

Zhu, Z., Ochoa, A. J., Schnabel, S., Hamze, F., & Katzgraber, H. G. (2016) · Physical Review A · doi:10.1103/physreva.93.012317 · Cited by 74 · see citing works

Optimizing Aircraft Trajectories with Multiple Cruise Altitudes in the Presence of Winds

Ng, H. K., Sridhar, B., & Grabbe, S. R. (2014) · Journal of Aerospace Information Systems · doi:10.2514/1.i010084 · Cited by 61 · see citing works

Constraint Programming and Combinatorial Optimisation in Numberjack

Hébrard, E., O’Mahony, E., & O’Sullivan, B. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13520-0_22 · Cited by 39 · see citing works

Collision avoidance of mobile robots by using initial time delays

Wang, X., Kloetzer, M., Mahulea, C., & Silva, M. (2015) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2015.7402221 · Cited by 28 · see citing works

Parametrized Families of Hard Planning Problems from Phase Transitions

Rieffel, E. G., Venturelli, D., Do, M., Hen, I., & Frank, J. (2014) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v28i1.9044 · Cited by 23 · see citing works

DECONFLICTING WIND-OPTIMAL AIRCRAFT TRAJECTORIES IN NORTH ATLANTIC OCEANIC AIRSPACE

Rodionova, O. K., Delahaye, D., Sridhar, B., & Ng, H. K. (2016) · HAL · Cited by 7 · see citing works

A Comparison Framework for Conflict Detection and Resolution Multi Agent Modeling Methods in Air Traffic Management

Emami, H. (2012) · International Journal of Information Technology Control and Automation · doi:10.5121/ijitca.2012.2405 · Cited by 1 · see citing works

Quantum annealing for industry applications: introduction and review

Yarkoni, S., Raponi, E., Bäck, T., & Schmitt, S. (2022) · Reports on Progress in Physics · doi:10.1088/1361-6633/ac8c54 · Cited by 341 · see citing works

A Novel Gate Resource Allocation Method Using Improved PSO-Based QEA

Deng, W., Xu, J., Zhao, H., & Song, Y. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.3025796 · Cited by 338 · see citing works

Reverse quantum annealing approach to portfolio optimization problems

Venturelli, D., & Kondratyev, A. (2019) · Quantum Machine Intelligence · doi:10.1007/s42484-019-00001-w · Cited by 233 · see citing works

Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems

Willsch, D., Willsch, M., Gonzalez Calaza, C. D., Jin, F., De Raedt, H., Svensson, M., & Michielsen, K. (2022) · Quantum Information Processing · doi:10.1007/s11128-022-03476-y · Cited by 114 · see citing works

Benchmarking Quantum Annealing Controls with Portfolio Optimization

Grant, E., Humble, T. S., & Stump, B. (2021) · Physical Review Applied · doi:10.1103/physrevapplied.15.014012 · Cited by 90 · see citing works

Domain wall encoding of discrete variables for quantum annealing and QAOA

Chancellor, N. (2019) · Quantum Science and Technology · doi:10.1088/2058-9565/ab33c2 · Cited by 90 · see citing works

Domain wall encoding of integer variables for quantum annealing and QAOA [dataset]

Chancellor, N. (2019) · Durham Research Online (Durham University) · doi:10.15128/r27d278t029 · Cited by 75 · see citing works

Flight Gate Assignment with a Quantum Annealer

Stollenwerk, T., Lobe, E., & Jung, M. H. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-14082-3_9 · Cited by 58 · see citing works

Implementation of Quantum Annealing: A Systematic Review

Yulianti, L. P., & Surendro, K. (2022) · IEEE Access · doi:10.1109/access.2022.3188117 · Cited by 61 · see citing works

Shaping the Future of the Application of Quantum Computing in Intelligent Transportation System

Wang, S., Pei, Z., Wang, C., & Wu, J. (2021) · Intelligent and Converged Networks · doi:10.23919/icn.2021.0019 · Cited by 54 · see citing works

A Quantum Annealer for Subset Feature Selection and the Classification of Hyperspectral Images

Otgonbaatar, S., & Datcu, M. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3095377 · Cited by 54 · see citing works

Cooperative Co-Evolution for Large-Scale Multiobjective Air Traffic Flow Management

Guo, T., Mei, Y., Tang, K., & Du, W. (2023) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2023.3328886 · Cited by 51 · see citing works

Agile Earth Observation Satellite Scheduling With a Quantum Annealer

Stollenwerk, T., Michaud, V., Lobe, E., Picard, M., Basermann, A., & Botter, T. (2021) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2021.3088490 · Cited by 49 · see citing works

Quantum Annealing versus Digital Computing

Jünger, M., Lobe, E., Mutzel, P., Reinelt, G., Rendl, F., Rinaldi, G., & Stollenwerk, T. (2021) · ACM Journal of Experimental Algorithmics · doi:10.1145/3459606 · Cited by 51 · see citing works

A Knee-Guided Evolutionary Algorithm for Multi-Objective Air Traffic Flow Management

Guo, T., Mei, Y., Tang, K., & Du, W. (2023) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2023.3281810 · Cited by 43 · see citing works

Multi-car paint shop optimization with quantum annealing

Yarkoni, S., Alekseyenko, A., Streif, M., Dollen, D. V., Neukart, F., & Bäck, T. (2021) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce52317.2021.00019 · Cited by 43 · see citing works

Hybrid quantum ResNet for car classification and its hyperparameter optimization

Sagingalieva, A., Kordzanganeh, M., Kurkin, A., Melnikov, A., Kuhmistrov, D., Perelshtein, M. R., Melnikov, A., Skolik, A., & Dollen, D. V. (2023) · Quantum Machine Intelligence · doi:10.1007/s42484-023-00123-2 · Cited by 54 · see citing works

An Interactive Conflict Solver for Learning Air Traffic Conflict Resolutions

Tran, P. N., Pham, D.-T., Goh, S. K., Alam, S., & Dương, V. (2020) · Journal of Aerospace Information Systems · doi:10.2514/1.i010807 · Cited by 42 · see citing works

Performance of Domain-Wall Encoding for Quantum Annealing [dataset]

Chen, J., & Chancellor, N. (2021) · Durham Research Online (Durham University) · doi:10.15128/r11j92g748d · Cited by 43 · see citing works

Energetic Perspective on Rapid Quenches in Quantum Annealing

Callison, A., Festenstein, M. Z., Chen, J., Nita, L., Kendon, V. M., & Chancellor, N. (2021) · PRX Quantum · doi:10.1103/prxquantum.2.010338 · Cited by 36 · see citing works

Deep reinforcement learning based path stretch vector resolution in dense traffic with uncertainties

Pham, D.-T., Tran, P. N., Alam, S., Duong, V., & Delahaye, D. (2021) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2021.103463 · Cited by 36 · see citing works

Approximate approximation on a quantum annealer

Sax, I., Feld, S., Zielinski, S., Gabor, T., Linnhoff–Popien, C., & Mauerer, W. (2020) · ACM International Conference on Computing Frontiers (CF) · doi:10.1145/3387902.3392635 · Cited by 33 · see citing works

Toward Smart Skies: Reviewing the State of the Art and Challenges for Intelligent Air Transportation Systems (IATS)

Wandelt, S., & Zheng, C. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3415588 · Cited by 32 · see citing works

How to Solve Combinatorial Optimization Problems Using Real Quantum Machines: A Recent Survey

Heng, S., Kim, D., Kim, T.-K., & Han, Y. (2022) · IEEE Access · doi:10.1109/access.2022.3218908 · Cited by 33 · see citing works

Solving the resource constrained project scheduling problem with quantum annealing

Armas, L. F. P., Creemers, S., & Deleplanque, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-67168-6 · Cited by 33 · see citing works

Toward Quantum Gate-Model Heuristics for Real-World Planning Problems

Stollenwerk, T., Hadfield, S., & Wang, Z. (2020) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2020.3030609 · Cited by 29 · see citing works

Quantum Combinatorial Optimization in the NISQ Era: A Systematic Mapping Study

Gemeinhardt, F., Garmendia, A., Wimmer, M., Weder, B., & Leymann, F. (2024) · ACM Computing Surveys · doi:10.1145/3620668 · Cited by 22 · see citing works

Trajectory-User Link with Attention Recurrent Networks

Sun, T., Xu, Y., Wang, F., Wu, L., Qian, T., & Shao, Z. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412453 · Cited by 22 · see citing works

Towards conformal automation in air traffic control: Learning conflict resolution strategies through behavior cloning

Guleria, Y., Pham, D.-T., Alam, S., Tran, P. N., & Durand, N. (2023) · Advanced Engineering Informatics · doi:10.1016/j.aei.2023.102273 · Cited by 21 · see citing works

Quantum Annealing Approach for the Optimal Real-time Traffic Control using QUBO

Singh, A., Lin, C.-Y., Huang, C.-I., & Lin, F. (2021) · ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) · doi:10.1109/snpd51163.2021.9704985 · Cited by 21 · see citing works

Quantum adiabatic machine learning by zooming into a region of the energy surface

Zlokapa, A., Mott, A., Job, J., Vlimant, J.-R., Lidar, D. A., & Spiropulu, M. (2020) · Physical Review A · doi:10.1103/physreva.102.062405 · Cited by 22 · see citing works

Quantum annealing-aided design of an ultrathin-metamaterial optical diode

Kim, S., Park, S.-J., Moon, S., Zhang, Q., Hwang, S., Kim, S.-K., Luo, T., & Lee, E. (2024) · Nano Convergence · doi:10.1186/s40580-024-00425-6 · Cited by 20 · see citing works

Minor Embedding in Broken Chimera and Pegasus Graphs is NP-complete

Lobe, E., & Lutz, A. (2021) · Theoretical Computer Science · doi:10.1016/j.tcs.2023.114369 · Cited by 21 · see citing works

Quantum Algorithms Using Infeasible Solution Constraints for Collision-Avoidance Route Planning

Li, Q., Huang, Z., Jiang, W., Tang, Z., & Song, M. (2024) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2024.3476156 · Cited by 21 · see citing works

A Symbolic Approach to Discrete Structural Optimization Using Quantum Annealing

Wils, K., & Chen, B. (2023) · Mathematics · doi:10.3390/math11163451 · Cited by 20 · see citing works

Embedding of complete graphs in broken Chimera graphs

Lobe, E., Schürmann, L., & Stollenwerk, T. (2020) · Quantum Information Processing · doi:10.1007/s11128-021-03168-z · Cited by 23 · see citing works

An advanced quantum support vector machine for power quality disturbance detection and identification

Wang, Q., Yu, J. Z., Li, X., Li, Y., Liu, H., Zhang, K.-J., Liu, H., & Cheng, L. (2024) · EPJ Quantum Technology · doi:10.1140/epjqt/s40507-024-00283-5 · Cited by 19 · see citing works

Assessing and advancing the potential of quantum computing: A NASA case study

Rieffel, E. G., Asanjan, A. A., Alam, M. S., Anand, N., Bernal, D. E., Block, S., Brady, L. T., Cotton, S., Izquierdo, Z. G., Grabbe, S. R., et al. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.06.012 · Cited by 20 · see citing works

Parity Quantum Optimization: Benchmarks

FELLNER, M. J., Ender, K., ter Hoeven, R., & Lechner, W. (2023) · Quantum · doi:10.22331/q-2023-03-17-952 · Cited by 23 · see citing works

Optimal Flight-Gate Assignment on a Digital Quantum Computer

Chai, Y., Funcke, L., Hartung, T., Jansen, K., Kühn, S., Stornati, P., & Stollenwerk, T. (2023) · Physical Review Applied · doi:10.1103/physrevapplied.20.064025 · Cited by 17 · see citing works

Experimental test of search range in quantum annealing

Chancellor, N., & Kendon, V. M. (2021) · Physical Review A · doi:10.1103/physreva.104.012604 · Cited by 15 · see citing works

Variational Quantum Algorithm Applied to Collision Avoidance of Unmanned Aerial Vehicles

Huang, Z., Li, Q., Zhao, J., & Song, M. (2022) · Entropy · doi:10.3390/e24111685 · Cited by 16 · see citing works

Accuracy and minor embedding in subqubo decomposition with fully connected large problems: a case study about the number partitioning problem

Asproni, L., Caputo, D., Silva, B., Fazzi, G., & Magagnini, M. (2020) · Quantum Machine Intelligence · doi:10.1007/s42484-020-00014-w · Cited by 16 · see citing works

A Systematic Mapping Study on Quantum and Quantum-inspired Algorithms in Operations Research

Gomes, C., Fernandes, J. P., Falcão, G., Kar, S., & TAYUR, S. R. (2024) · ACM Computing Surveys · doi:10.1145/3700874 · Cited by 15 · see citing works

Parity Quantum Optimization: Encoding Constraints

Drieb-Schön, M., Ender, K., Javanmard, Y., & Lechner, W. (2023) · Quantum · doi:10.22331/q-2023-03-17-951 · Cited by 18 · see citing works

Encoding trade-offs and design toolkits in quantum algorithms for discrete optimization: coloring, routing, scheduling, and other problems

Sawaya, N. P. D., Schmitz, A. T., & Hadfield, S. (2023) · Quantum · doi:10.22331/q-2023-09-14-1111 · Cited by 16 · see citing works

Quantum computing for space applications: a selective review and perspectives

Torta, P., Casati, R., Bruni, S., Mandarino, A., & Prati, E. (2025) · EPJ Quantum Technology · doi:10.1140/epjqt/s40507-025-00369-8 · Cited by 13 · see citing works

Investigating the Chinese postman problem on a quantum annealer

Siloi, I., Carnevali, V., Pokharel, B., Fornari, M., & Felice, R. D. (2021) · Quantum Machine Intelligence · doi:10.1007/s42484-020-00031-9 · Cited by 15 · see citing works

Characterization of QUBO reformulations for the maximum k-colorable subgraph problem

Quintero, R. A., Bernal, D. E., Tamás Terlaky, B., & Zuluaga, L. F. (2022) · Quantum Information Processing · doi:10.1007/s11128-022-03421-z · Cited by 13 · see citing works

From Ansätze to Z-Gates: A NASA View of Quantum Computing

Rieffel, E. G., Hadfield, S., Hogg, T., Mandrà, S., Marshall, J., Mossi, G., O’Gorman, B., Plamadeala, E., Tubman, N. M., Venturelli, D., et al. (2019) · Advances in parallel computing · doi:10.3233/apc190010 · Cited by 13 · see citing works

Fluctuation-guided search in quantum annealing

Chancellor, N. (2020) · Physical Review A · doi:10.1103/physreva.102.062606 · Cited by 11 · see citing works

UAV Swarm Path Planning

James, S., Raheb, R., & Hudak, A. (2020) · Integrated Communications, Navigation and Surveillance Conference (ICNS) · doi:10.1109/icns50378.2020.9223005 · Cited by 12 · see citing works

Solving the Shipment Rerouting Problem with Quantum Optimization Techniques

Yarkoni, S., Huck, A., Schülldorf, H., Speitkamp, B., Tabrizi, M. S., Leib, M., Bäck, T., & Neukart, F. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87672-2_33 · Cited by 12 · see citing works

Quantum computing approach to railway dispatching and conflict management optimization on single-track railway linesPreprint

Domino, K., Koniorczyk, M., Krawiec, K., Jałowiecki, K., & Gardas, B. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.08227 · Cited by 15 · see citing works

A Review of Research on Flight Delay Propagation: Current Situation and Prospect

Li, N., & Yao, H. (2025) · Journal of Advanced Transportation · doi:10.1155/atr/4851103 · Cited by 10 · see citing works

Dynamic Path Planning for Unmanned Aerial Vehicles Under Deadline and Sector Capacity Constraints

Vaidhun, S., Guo, Z., Bian, J., Xiong, H., & Das, S. K. (2021) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2021.3122743 · Cited by 10 · see citing works

Semi-supervised time series classification method for quantum computing

Yarkoni, S., Kleshchonok, A., Dzerin, Y., Neukart, F., & Hilbert, M. (2021) · Quantum Machine Intelligence · doi:10.1007/s42484-021-00042-0 · Cited by 10 · see citing works

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 · see citing works

Efficient Hamiltonian Reduction for Quantum Annealing on SatCom Beam Placement Problem

Dinh, T. Q., Dau, S. H., Lagunas, E., & Chatzinotas, S. (2023) · International Conference on Communications · doi:10.1109/icc45041.2023.10279813 · Cited by 9 · see citing works

Applied Game Theory to Enhance Air Traffic Control in 3D Airspace

Rangrazjeddi, A., González, A. D., & Barker, K. (2023) · Journal of Optimization Theory and Applications · doi:10.1007/s10957-023-02165-9 · Cited by 8 · see citing works

Path Planning for Critical ATM/UTM Areas

James, S., & Raheb, R. (2019) · IEEE/AIAA Digital Avionics Systems Conference (DASC) · doi:10.1109/dasc43569.2019.9081662 · Cited by 8 · see citing works

A QUBO formulation for top-τ eigencentrality nodes

Akrobotu, P. D., James, T. E., Negre, C. F. A., & Mniszewski, S. M. (2022) · PLoS ONE · doi:10.1371/journal.pone.0271292 · Cited by 8 · see citing works

Challenges for Quantum Software Engineering: An Industrial Application Scenario Perspective

Carbonelli, C., Felderer, M., Jung, M., Lobe, E., Lochau, M., Luber, S. M., Mauerer, W., Ramler, R., Schaefer, I., & Schroth, C. (2024) · Springer eBooks · doi:10.1007/978-3-031-64136-7_12 · Cited by 7 · see citing works

Cutting-Edge Trajectory Optimization through Quantum Annealing

Carbone, A., Grossi, F. D., & Spiller, D. (2023) · Applied Sciences · doi:10.3390/app132312853 · Cited by 7 · see citing works

Quantum optimization with linear Ising penalty functions for customer data science

Mirkarimi, P., Shukla, I., Hoyle, D. C., Williams, R., & Chancellor, N. (2024) · Physical Review Research · doi:10.1103/physrevresearch.6.043241 · Cited by 7 · see citing works

Petri Net Modeling for Ising Model Formulation in Quantum Annealing

Nakamura, M., Kaneshima, K., & Yoshida, T. (2021) · Applied Sciences · doi:10.3390/app11167574 · Cited by 7 · see citing works

Quantum-Inspired Firefly Algorithm: An Enhanced Approach To Traffic Signal Optimization

Upare, D. M., Baddi, T. Y., Benni, R., & Patil, P. R. (2024) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt61001.2024.10726156 · Cited by 6 · see citing works

QUBO Decision Tree: Annealing Machine Extends Decision Tree Splitting

Yawata, K., Osakabe, Y., Okuyama, T., & Asahara, A. (2022) · IEEE International Conference on Knowledge Graph (ICKG) · doi:10.1109/ickg55886.2022.00052 · Cited by 6 · see citing works

Improving Quantum Annealing Performance on Embedded Problems

(2020) · Supercomputing Frontiers and Innovations · doi:10.14529/jsfi200403 · Cited by 6 · see citing works

Transcription and optimization of an interplanetary trajectory through quantum annealing

Grossi, F. D., Carbone, A., Spiller, D., Ottaviani, D., Mengoni, R., & Circi, C. (2025) · Astrodynamics · doi:10.1007/s42064-024-0216-6 · Cited by 5 · see citing works

Hybrid Quantum Annealing with Innovative Trend Ratio Model for Portfolio Optimization

Chou, Y., Wu, C.-H., Huang, P.-S., Kuo, S., Jiang, Y.-C., Kuo, S., & Chang, C. (2024) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec60901.2024.10612069 · Cited by 7 · see citing works

Graph Minor Embedding Can Affect Sampling Degenerate Ground States Using Quantum Annealing

Maruyama, N., Ohzeki, M., & Tanaka, K. (2025) · Journal of the Physical Society of Japan · doi:10.7566/jpsj.95.013002 · Cited by 5 · see citing works

Quantum Annealing in the NISQ Era: Railway Conflict Management

Domino, K., Koniorczyk, M., Krawiec, K., Jałowiecki, K., Deffner, S., & Gardas, B. (2023) · Entropy · doi:10.3390/e25020191 · Cited by 5 · see citing works

Impact of Packet Loss to the Motion of Autonomous UAV Swarms

James, S., Raheb, R., & Hudak, A. (2020) · IEEE/AIAA Digital Avionics Systems Conference (DASC) · doi:10.1109/dasc50938.2020.9256561 · Cited by 5 · see citing works

Toward a standardized methodology for constructing quantum computing use casesPreprint

Chancellor, N., CUMMING, R. L., & Thomas, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.05846 · Cited by 5 · see citing works

An Ising machine formulation for design updates in topology optimization of flow channels

Suzuki, Y., Aoki, S., Key, F., Endo, K., Matsuda, Y., Tanaka, S., Behr, M., & Muramatsu, M. (2026) · Engineering With Computers · doi:10.1007/s00366-025-02265-2 · Cited by 3 · see citing works

QUBO formulation for aircraft load optimization

Gatti, L., Sotelo, R., Orihuela, J.-D., Gibert, D., D’ambrosio, R., & Fuidio, F. (2024) · Quantum Information Processing · doi:10.1007/s11128-024-04569-6 · Cited by 4 · see citing works

Traffic Signal Optimization in Large-Scale Urban Road Networks: An Adaptive-Predictive Controller Using Ising Models

Inoue, D., Yamashita, H., Aihara, K., & Yoshida, H. (2024) · IEEE Access · doi:10.1109/access.2024.3514162 · Cited by 4 · see citing works

Next Generation of Intelligent Cities

Varadharajan, V., & Rian Leevinson, J. (2020) · Advances in civil and industrial engineering book series · doi:10.4018/978-1-7998-5062-5.ch004 · Cited by 4 · see citing works

Applying Quantum Annealing for Shift Scheduling Problem for Call Centers

Hamada, N., Saito, K., & Kawashima, H. (2023) · International Journal of Networking and Computing · doi:10.15803/ijnc.13.1_2 · Cited by 4 · see citing works

Ising-Based Kernel Clustering

Kumagai, M., Komatsu, K., Sato, M., & Kobayashi, H. (2023) · Algorithms · doi:10.3390/a16040214 · Cited by 4 · see citing works

Quantum annealing-based route optimization for commercial AGV operating systems in large-scale logistics warehouses

Quang, T. N., Matsuyama, K., Shimizu, K., Sugano, H., Kurimoto, E., Miki, M., Suzuki, J., Chen, Z., Waidyasooriya, H. M., Hariyama, M., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-28481-w · Cited by 6 · see citing works

Evaluating the practicality of quantum optimization algorithms for prototypical industrial applications

Vandelli, M., Lignarolo, A., Cavazzoni, C., & Dragoni, D. (2024) · Quantum Information Processing · doi:10.1007/s11128-024-04560-1 · Cited by 2 · see citing works

Single photon coherent Ising machines for constrained optimization problems

Kumagai, M., Inui, Y., Ng, E., Kako, S., Komatsu, K., Kobayashi, H., & Yamamoto, Y. (2025) · Quantum Science and Technology · doi:10.1088/2058-9565/addde5 · Cited by 3 · see citing works

Quantum Optimization for Closed-Loop Scheduling of Earth Observation Satellite Formation

Marchioli, V., Boggio, M., Volpe, D., Massotti, L., & Novara, C. (2025) · SN Computer Science · doi:10.1007/s42979-025-04252-2 · Cited by 3 · see citing works

Mapping state transition susceptibility in quantum annealing

Pelofske, E. (2023) · Physical Review Research · doi:10.1103/physrevresearch.5.013224 · Cited by 3 · see citing works

Investigating the Characteristics of Ising Machines

Komatsu, K., Onoda, M., Kumagai, M., & Kobayashi, H. (2023) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce57702.2023.00108 · Cited by 3 · see citing works

An Agent-Based Approach for Air Traffic Conflict Resolution in a Flow-Centric Airspace

Guleria, Y., Pham, D.-T., & Alam, S. (2023) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc57777.2023.10422292 · Cited by 3 · see citing works

QUBO Formulations of Combinatorial Optimization Problems for Quantum Computing Devices

Quintero, R. A., & Zuluaga, L. F. (2022) · Encyclopedia of Optimization · doi:10.1007/978-3-030-54621-2_853-1 · Cited by 3 · see citing works

Solving the Resource-Constrained Project Scheduling Problem (RCPSP) with Quantum AnnealingPreprint

Armas, L. F. P., Creemers, S., & Deleplanque, S. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4689017 · Cited by 3 · see citing works

Optimizing Flight Routes for Better Fuel Efficiency and Optimal Path using Grover's Algorithm & QAOA Algorithm - Quantum Computing

Khan, M. I., Govindharaj, I., Sathishkumar, R., Jenifer, D. H., Maeghasree, T., & Yohini, K. (2024) · International Conference on System, Computation, Automation and Networking (ICSCAN) · doi:10.1109/icscan62807.2024.10894075 · Cited by 2 · see citing works

Solving large break minimization problems in a mirrored double round-robin tournament using quantum annealing

Kuramata, M., Katsuki, R., & Nakata, K. (2021) · PLoS ONE · doi:10.1371/journal.pone.0266846 · Cited by 3 · see citing works

Qobra: Fast Verification of Transactional Serializability with Quantum Annealing

Hamada, N., Saito, K., & Kawashima, H. (2023) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata59044.2023.10386188 · Cited by 2 · see citing works

Quantum Software Ecosystem Design

Basermann, A., Epping, M., Fauseweh, B., Felderer, M., Lobe, E., Röhrig-Zöllner, M., Schmiedinghoff, G., Schuhmacher, P. K., Setyawati, Y., & Weinert, A. (2024) · Springer eBooks · doi:10.1007/978-3-031-64136-7_7 · Cited by 3 · see citing works

A Review of Quantum Machine Learning Applications

Marcozzi, M., Filatovas, E., & Paulavičius, R. (2025) · Studies in computational intelligence · doi:10.1007/978-3-031-88486-3_7 · Cited by 2 · see citing works

SWIFT-FMQA: Enhancing Factorization Machine With Quadratic-Optimization Annealing via Sliding Window

Nakano, M., Seki, Y., Kikuchi, S., & Tanaka, S. (2026) · IEEE Access · doi:10.1109/access.2026.3655591 · Cited by 2 · see citing works

Performance of Domain-Wall Encoding for Quantum Annealing

Chen, J., Stollenwerk, T., & Chancellor, N. (2021) · IEEE Transactions on Quantum Engineering · doi:10.1109/tqe.2021.3094280 · Cited by 2 · see citing works

Advancements in Quantum Algorithms for Solving Complex Optimization ProblemsPreprint

Adediran, E., Fatoki, I., & Ogunyinka, T. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.5015789 · Cited by 2 · see citing works

A Quadratic Unconstrained Binary Optimization (QUBO) Model for Elevation‐Aware Vehicle Routing: Optimizing Fuel Consumption and Traffic Congestion

Suzuki, T., & Tomono, T. (2026) · Advanced Quantum Technologies · doi:10.1002/qute.202500660 · Cited by 1 · see citing works

Quantum computing in transport science: a review

Niu, C., Irannezhad, E., Myers, C. R., & Dixit, V. (2026) · Transportation Letters · doi:10.1080/19427867.2026.2640414 · Cited by 1 · see citing works

Quantum Annealing for Air Traffic Management

Stollenwerk, T. (2016) · elib (German Aerospace Center)

Quantum Annealing for Flight Gate Assignment

Stollenwerk, T., Lobe, E., & Jung, M. H. (2018) · elib (German Aerospace Center)

Flight Gate Assignment with a Quantum Annealer

Stollenwerk, T., Lobe, E., & Jung, M. H. (2018) · elib (German Aerospace Center) · doi:10.48550/arxiv.1811.09465 · Cited by 4 · see citing works

Quantum Annealing in the NISQ Era: Railway Conflict Management

Domino, K., Koniorczyk, M., Krawiec, K., Jałowiecki, K., Deffner, S., & Gardas, B. (2023) · Entropy · doi:10.3390/e25020191 · Cited by 5 · see citing works

Optimal control of traffic signals using quantum annealing

Hussain, H., Javaid, M. B., Khan, F. S., Dalal, A., & Khalique, A. (2020) · Quantum Information Processing · doi:10.1007/s11128-020-02815-1 · Cited by 66 · see citing works