Publications

The following lists are updated sporadically. For automatically updates lists, see Google Scholar and arXiv.

Current work (submitted papers, technical reports):

  • Z. Chen, G. Nannicini. A simple lower bound for the complexity of estimating partition functions on a quantum computer. Arxiv paper 2404.02414.
  • A. Abbas et al. (see detailed CV for full list of coauthors). Quantum optimization: potential, challenges, and the path forward. Arxiv paper 2312.02279.
  • B. Augustino, J. Leng, G. Nannicini, T. Terlaky, X. Wu. A quantum central path algorithm for linear optimization. Arxiv paper 2311.03977.
  • B. Augustino, G. Nannicini, T. Terlaky, L. Zuluaga. Solving the semidefinite relaxation of QUBOs in matrix multiplication time, and faster with a quantum computer. Arxiv paper 2301.04237.
  • N. Halman, G. Nannicini. Fully polynomial-time approximation schemes for
    robust multistage decision making. Under review.
  • J.J. Torres, G. Nannicini, E. Traversi, R.~Wolfler-Calvo. A trust-region framework for derivative-free mixed-integer optimization. Under review.

Journal:

  • B. Augustino, G. Nannicini, T. Terlaky, L. Zuluaga. Quantum interior point methods for semidefinite optimization. Quantum, 2023, paper 2112.06025.
  • A. Lodi, E. Malaguti, M. Monaci, G. Nannicini, P. Paronuzzi. A solution algorithm for chance-constrained problems with integer second-stage recourse decisions. Mathematical Programming, 205(1-2):269-301, 2024. Optimization online, paper 8514.
  • G. Nannicini. Fast quantum subroutines for the simplex method. Operations Research. 72(2):763-780, 2022. Arxiv paper 1910.10649. Extended version of IPCO 2021 paper.
  • G. Nannicini, L. S. Bishop, O. Gunluk, P. Jurcevic. Optimal qubit assignment and routing via integer programming. ACM Transactions on Quantum Computing, 4(1):1-31, 2023. Arxiv paper 2106.06446.
  • S. Arunachalam, V. Havlicek, G. Nannicini, K. Temme, P. Wocjan. Simpler (classical) and faster (quantum) algorithms for Gibbs partition functions. Quantum, 2022, paper 2009.11270.
  • N. Halman, G. Nannicini. Fully polynomial-time (Σ-Π) approximation schemes for continuous nonlinear newsvendor and continuous stochastic dynamic programs. Mathematical Programming, 195(1):183-242, 2022. Optimization Online paper 5276.
  • G. Nannicini. On the implementation of a global optimization method for mixed-variable problems. Open Journal of Mathematical Optimization, 2:1-25, 2021. Arxiv paper 2009.02183.
  • P. Jurcevic, A. Javadi-Abhari, L. S. Bishop, I. Lauer, D. F. Bogorin, M. Brink, L. Capelluto, O. Günlúk, T. Itoko, N. Kanazawa, A. Kandala, G. A. Keefe, K. Kruslich, W. Landers, E. P.. Lewandowski, D. T. McClure, G. Nannicini, A. Narasgond, H. M. Nayfeh, E. Pritchett, M. B. Rothwell, S. Srinivasan, N. Sundaresan, C. Wang, K. X. Wei, C. J. Wood, J.-B. Yau, E. J. Zhang, O. E. Dial, J. M. Chow, J. M. Gambetta. Demonstration of quantum volume 64 on a superconducting quantum computing system. Quantum Science and Technology, 6.2:025020, 2021. Arxiv paper 2008.08571.
  • G. Nannicini, E. Traversi, R. Wolfler-Calvo. A Benders squared (B^2) algorithm for infinite horizon stochastic linear programs. Mathematical Programming Computation, 12(4):645-681, 2021. Journal link
  • P. Barkoutsos, G. Nannicini, A. Robert, I. Tavernelli, S. Worner. Improving variational quantum optimization using CVaR. Quantum, paper 1907.04769.
  • G. Nannicini, G. Sartor, E. Traversi, R. Wolfler-Calvo. An exact algorithm for robust influence maximization. Mathematical Programming B, 183(1):419–453, 2020. Optimization Online paper 7268. Extended version of IPCO 2019 paper.
  • A. Lodi, E. Malaguti, G. Nannicini and D. Thomopulos. Nonlinear chance-constrained problems with applications to hydro scheduling. Mathematical Programming B, 191(1):405-444, 2022. Journal link
  • G. Nannicini. An introduction to quantum computing, without the physics. SIAM Review, 62(4):936-981, 2020. Arxiv paper 1708.03684.
  • N. Halman, G. Nannicini. Toward breaking the curse of dimensionality: an FPTAS for stochastic dynamic programs with scalar state via recursive linear programming. SIAM Journal on Optimization, 29(2):1131–1163, 2019. Arxiv paper 1811:11680. Journal link
  • G. Nannicini. Performance of hybrid quantum/classical variational heuristics for combinatorial optimization. Physical Review E, 99:013304, 2019. Arxiv paper 1805.12037. Journal link
  • E. Pednault, J. A. Gunnels, G. Nannicini, L. Horesh, R. Wisnieff. Leveraging secondary storage to simulate deep 54-qubit Sycamore circuits. Arxiv paper 1910.09534
  • A. Costa and G. Nannicini. RBFOpt: an open-source library for black-box optimization with costly function evaluations. Mathematical Programming Computation, 10(4):597–629, 2018. Optimization Online paper 4538.   Journal link
  • N. Halman, G. Nannicini and J. Orlin. On the complexity of energy storage problems. Discrete Optimization, 28:31-53, 2018.   Journal link
  • A. Costa, E. Di Buccio, M. Melucci and G. Nannicini. Efficient parameter estimation for information retrieval using black-box optimization. IEEE Transactions on Knowledge and Data Engineering, 30(7):1240-1253, 2018. Journal link
  • E. Pednault, J. A. Gunnels, G. Nannicini, L. Horesh, T. Magerlein, E. Solomonik, E. Draeger, E. Holland, R. Wisnieff. Pareto-efficient quantum circuit simulation using tensor contraction deferral. Arxiv paper 1710.05867.
  • A. Fokoue, G. Diaz, G. Nannicini, H. Samulowitz. An effective algorithm for hyperparameter optimization of neural networks. IBM Journal of Research and Development,  61(4-5), 2017.  Journal link
  • C. D’ambrosio, G. Nannicini, G. Sartor. MILP models for the selection of a small set of well-distributed points. Operations Research Letters, 45(1):56-62, 2017.  Journal link
  • J. Kalikka, X. Zhou, J. Behera, G. Nannicini, R. Simpson. Evolutionary design of interfacial phase change van der Waals heterostructures. Nanoscale, 8(42):18212-18220, 2016. Journal link
  • T. Wortmann, A. Costa, G. Nannicini, T. Schroepfer. Advantages of surrogate models for architectural design optimization. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 29(4):471-481, 2015. Journal link
  • N. Halman, G. Nannicini and J. Orlin. A computationally efficient FPTAS for convex stochastic dynamic programming. SIAM Journal on Optimization, 25(1):317-350, 2015.  Journal link. Extended version of of ESA 2013 paper.
  • G. Cornuejols, F. Margot and G. Nannicini. On the safety of Gomory cut generators. Mathematical Programming Computation, 5(4):345-395, 2013.  Journal link
  • E. Balas, G. Cornuejols, T. Kis and G. Nannicini. Combining Lift-and-Project and Reduce-and-Split. INFORMS Journal on Computing, 25(3):475-487, 2013.  Journal link
  • G. Cornuejols, C. Michini, G. Nannicini. How tight is the corner relaxation? Insights gained from the stable set problem. Discrete Optimization, 9(2):109-121, 2012. Selected by the Editorial Board for the 10 Year Anniversary Virtual Special Issue as an “excellent paper […] over the last decade”.  Journal link
  • G. Nannicini and P. Belotti. Rounding based heuristics for nonconvex MINLPs. Mathematical Programming Computation, 4(1):1-31, 2012.  Journal link
  • D. Delling and G. Nannicini. Core routing on dynamic time-dependent road networks. INFORMS Journal on Computing, 24(2):187-201, 2012.  Journal link. Extended version of ISAAC 2008 paper.
  • G. Nannicini, D. Delling, D. Schultes and L. Liberti. Bidirectional A* search on time-dependent road networks. Networks, 59(2):240-251, 2012. Winner of the 2012 Glover-Klingman prize.  Journal link. Extended version of WEA 2008 paper.
  • L. Liberti, G. Nannicini and N. Mladenovic. A recipe for finding good solutions to MINLPs. Mathematical Programming Computation, 3(4):349-390, 2011.  Journal link
  • G. Cornuejols and G. Nannicini. Practical strategies for generating rank-1 split cuts in mixed-integer linear programming. Mathematical Programming Computation, 3(4):281-318, 2011.  Journal link
  • G. Cornuejols, L. Liberti and G. Nannicini. Improved strategies for branching on general disjunctions. Mathematical Programming A, 130(2):225–247, 2011.  Journal link
  • G. Nannicini. Point-to-Point Shortest Paths on Dynamic Time-Dependent Road Networks (Ph.D. thesis abstract). 4OR, 8(3):327-330, 2010.  Journal link
  • G. Nannicini, P. Baptiste, G. Barbier, D. Krob, and L. Liberti. Fast paths in large-scale dynamic road networks. Computational Optimization and Applications, 45(1):143-158, 2010.  Journal link
  • G. Nannicini and L. Liberti. Shortest paths on dynamic graphs. International Transactions in Operational Research, 15:1-13, 2008. Journal link

Selected conference papers (that did not also appear in a journal):

  • J. van Apeldoorn, A. Cornelissen, A. Gilyen, G. Nannicini. Quantum tomography with state-preparation unitaries. SODA, 2023. Arxiv paper 2207.08800.
  • V. Austel. S. Dash, O. Gunluk, L. Horesh, L. Liberti, G. Nannicini, B. Schieber. Globally optimal symbolic regression. NIPS Symposium on Interpretable Machine Learning, 2017. Arxiv paper 1710.10720.
  • T. Wortmann, G. Nannicini. Optimization methods for architectural design. Proceedings of the 21st Annual Conference on Computer-Aided Architecture Design Research in Asia (CAADRIA 2016), 2016.
  • A. Costa, G. Nannicini, T. Schroepfer, T. Wortmann. Black-box optimization of lighting simulation in architectural design. Proceedings of Complex Systems Design & Management Asia, pages 27-39. Springer, 2015.
  • G. Nannicini, P. Belotti, J. Lee, J. Linderoth, F. Margot, A. W ̈achter. A probing algorithm for MINLP with failure prediction by SVM. Proceedings of CPAIOR 2011, volume 6697 of Lecture Notes in Computer Science, pages 154-169. Springer, 2011.
  • G. Nannicini and P. Belotti. Rounding-based heuristics for nonconvex MINLPs. Proceedings of EWMINLP, Marseille, 2010.
  • G. Nannicini, P. Baptiste, D. Krob, and L. Liberti. Fast computation of point-to-point paths on time-dependent road networks. Proceedings of COCOA 08, volume 5165 of Lecture Notes in Computer Science, pages 225-234. Springer, 2008.