Neng Fan

Associate Department Head of Systems and Industrial Engineering
Professor of Systems and Industrial Engineering
Professor, Applied Mathematics Graduate Interdisciplinary Program
Professor, Statistics Graduate Interdisciplinary Program
Member of the Graduate Faculty
Neng Fan

Engineering 312

520.621.6557
nfan@arizona.edu

Neng Fan is a professor of Systems and Industrial Engineering at the University of Arizona and a member of the Applied Mathematics-GIDP and Statistics-GIDP. He received his PhD degree from the Department of Industrial and Systems Engineering at the University of Florida. His research focuses on optimization under uncertainty and large-scale optimization and their applications in power systems, renewable energy integration, sustainable agriculture and healthcare. His research has been funded by the NSF, DOE, USDA and local industry partners. He is a member of INFORMS and a member of IISE.

Degrees

  • PhD Industrial and Systems Engineering
    • University of Florida, Gainesville, Florida, United States
  • MS Applied Math
    • Nankai University, China
  • BS Computational Math
    • Wuhan University, China

Interests

Teaching

Optimization, Operations Research, Probability and Statistics

Research

Optimization under uncertainty and large-scale optimization, and applications in power systems, renewable energy integration, sustainable agriculture, and healthcare

Selected Publications

Journals/Publications

  • Zhong, Z., Fan, N., & Wu, L. (2024). Multistage robust optimization for the day-ahead scheduling of hybrid thermal-hydro-wind-solar systems. Journal of Global Optimization, 88, 999--1034. doi:10.1007/s10898-023-01328-2.
  • Zhong, Z., Fan, N., & Wu, L. (2024). Multistage stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty. European Journal of Operational Research, 318(1), 179--199. doi:10.1016/j.ejor.2024.05.011.
  • Ruiz Duarte, J., & Fan, N. (2023). Operations of data centers with onsite renewables considering greenhouse gas emissions. Sustainable Computing: Informatics and Systems, 40, 100903. doi:10.1016/j.suscom.2023.100903.
  • Zhong, Z., Fan, N., & Wu, L. (2023). A hybrid robust-stochastic optimization approach for day-ahead scheduling of cascaded hydroelectric systems in restructured electricity market. European Journal of Operational Research, 306(2), 909--926. doi:10.1016/j.ejor.2022.06.061.
  • Zuniga Vazquez, D., Qiu, F., Fan, N., & Sharp, K. (2022). Wildfire mitigation plans in power systems: a literature review. IEEE Transactions on Power Systems, 37(5), 3540--3551. doi:10.1109/TPWRS.2022.3142086.
  • Gu, W., Fan, N., & Liao, H. (2021). Fitting aggregated phase-type distributions to the length-of-stay in intra-hospital patient transfers. Operations Research for Health Care, 29, 100291. doi:10.1016/j.orhc.2021.100291.
  • Gu, W., Fan, N., & Liao, H. (2021). Modeling the length-of-stay of patients with geriatric diseases or alcohol use disorder using phase-type distributions with covariates. IISE Transactions on Healthcare Systems Engineering, 11, 181--191. doi:10.1080/24725579.2020.1866715.
  • Karimi, S., Liao, H., & Fan, N. (2021). Flexible methods for reliability estimation using aggregate failure-time data. IISE Transactions, 53(1), 101-115. doi:10.1080/24725854.2020.1746869.
  • Zuniga Vazquez, D., Fan, N., Teegerstrom, T., Seavert, C., Summers, H., Sproul, E., & Quinn, J. (2021). Optimal production planning and machinery scheduling for semi-arid farms. Computers and Electronics in Agriculture, 187, 106288. doi:10.1016/j.compag.2021.106288.
  • Zuniga Vazquez, D., Sun, O., Fan, N., Sproul, E., Summers, H., Quinn, J., Khanal, S., Gutierrez, P., Mealing, V., Landies, A., Seavert, C., Teegerstrom, T., & Evancho, B. (2021). Integrating environmental and social impacts into optimal design of guayule and guar supply chains. Computers & Chemical Engineering, 146, 107223. doi:10.1016/j.compchemeng.2021.107223.
  • Ruiz Duarte, J., Fan, N., & Jin, T. (2020). Multi-process production scheduling with variable renewable integration and demand response. European Journal of Operational Research, 281(1), 186-200. doi:10.1016/j.ejor.2019.08.017.
  • Gu, W., Fan, N., & Liao, H. (2019). Evaluating readmission rates and discharge planning by analyzing the length-of-stay of patients. Annals of Operations Research, 276(1-2), 89-108. doi:10.1007/s10479-018-2957-1.
  • Sun, O., & Fan, N. (2019). Solving multistage PMU placement problem by integer programming and equivalent network design model. Journal of Global Optimization, 74(3), 477--493. doi:10.1007/s10898-018-0672-8.
  • Chen, R. L., Fan, N., Pinar, A., & Watson, J. (2017). Contingency-constrained unit commitment with post-contingency corrective recourse. Annals of Operations Research, 249(1), 381-407. doi:10.1007/s10479-014-1760-x.
  • Golari, M., Fan, N., & Jin, T. (2017). Multistage stochastic optimization for production-inventory planning with intermittent renewable energy. Production and Operations Management, 26(3), 409-425. doi:10.1111/poms.12657.
  • Guo, Z., Chen, R., Fan, N., & Watson, J. (2017). Contingency-constrained unit commitment with intervening time for system adjustments. IEEE Transactions on Power Systems, 32(4), 3049-3059. doi:10.1109/TPWRS.2016.2612680.
  • Wang, X., Fan, N., & Pardalos, P. M. (2017). Stochastic subgradient descent method for large-scale robust chance-constrained support vector machines. Optimization Letters, 11(5), 1013–1024. doi:10.1007/s11590-016-1026-4.
  • Zhang, P., & Fan, N. (2017). Analysis of budget for interdiction on multicommodity network flows. Journal of Global Optimization, 67(3), 495-525. doi:10.1007/s10898-016-0422-8.
  • Zhang, P., Fan, N., & Liu, W. (2017). Mixed integer programming with dose-volume constraints in intensity-modulated proton therapy. Journal of Applied Clinical Medical Physics, 18(5), 29–35. doi:10.1002/acm2.12130.
  • Dabkowski, M., Fan, N., & Breiger, R. (2016). Exploratory blockmodeling for one-mode, unsigned, deterministic networks using integer programming and structural equivalence. Social Networks, 47, 93--106.
  • Sadeghi, E., & Fan, N. (2016). On the minimum-cost lambda-edge-connected k-subgraph problem. Computational Management Science, 13(4), 571–596. doi:10.1007/s10287-016-0260-7.
  • Fan, N., & Watson, J. (2015). On integer programming models for the multi-channel PMU placement problem and their solution. Energy Systems, 6(1), 1--19.
  • Chen, R. L., Cohn, A., Fan, N., & Pinar, A. (2014). Contingency-risk informed power system design. IEEE Transactions on Power Systems, 29(5), 2087--2096.
  • Golari, M., Fan, N., & Wang, J. (2014). Two-stage stochastic optimal islanding operations under severe multiple contingencies in power grids. Electric Power Systems Research, 114, 68--77.
  • Huang, Y., Zheng, Q. P., Fan, N., & Aminian, K. (2014). Optimal scheduling for enhanced coal bed methane production through CO 2 injection. Applied Energy, 113, 1475--1483.
  • Fan, N., & Pardalos, P. M. (2012). Multi-way clustering and biclustering by the Ratio cut and Normalized cut in graphs. Journal of Combinatorial Optimization, 23(2), 224--251.
  • Fan, N., Izraelevitz, D., Pan, F., Pardalos, P. M., & Wang, J. (2012). A mixed integer programming approach for optimal power grid intentional islanding. Energy Systems, 3(1), 77--93.
  • Fan, N., Zheng, Q. P., & Pardalos, P. M. (2012). Robust optimization of graph partitioning involving interval uncertainty. Theoretical Computer Science, 447, 53--61.
  • Liu, H., Fan, N., & Pardalos, P. M. (2012). Generalized lagrange function and generalized weak saddle points for a class of multi-objective fractional optimal control problems. Journal of Optimization Theory and Applications, 154(2), 370--381.
  • Fan, N., & Pardalos, P. M. (2011). A rearrangement of adjacency matrix based approach for solving the crossing minimization problem. Journal of Combinatorial Optimization, 22(4), 747--762.
  • Fan, N., Xu, H., Pan, F., & Pardalos, P. M. (2011). Economic analysis of the N- k power grid contingency selection and evaluation by graph algorithms and interdiction methods. Energy Systems, 2(3-4), 313--324.
  • Fan, N., & Pardalos, P. M. (2010). Linear and quadratic programming approaches for the general graph partitioning problem. Journal of Global Optimization, 48(1), 57--71.