Faculty Directory

Kelly M. Sullivan

Kelly M. Sullivan

Associate Professor - ENGR

College of Engineering

(INEG)-Industrial Engineering

Phone: 479-575-2563

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Dr. Kelly Sullivan's research interests center on designing, maintaining, and securing complex systems.  His work focuses on advancing relevant knowledge in the areas of network optimization, interdiction, reliability, and integer programming.  He obtained his Ph.D. in Industrial and Systems Engineering from the University of Florida in 2012. He teaches courses in network optimization, operations research, and probability and statistics.

  • Network Optimization and Interdiction
  • Optimization in Reliability
  • Defense Applications
  • Homeland Security Applications

INEG 2313: Applied Probability and Statistics for Engineers I

INEG 2812H: Honors Research Experience I

INEG 3812H: Honors Research Experience II

INEG 4812H: Honors Research Experience III

INEG 3613: Introduction to Operations Research

INEG 6313: Network Optimization

  • B.S. Industrial Engineering, University of Arkansas (December 2006)
  • M.S. Industrial Engineering, University of Arkansas (August 2008)
  • Ph.D. Industrial and Systems Engineering, University of Florida (August 2012)

Papers Accepted or in Print

  1. Ahadi, K. and K. M. Sullivan.  Approximate Dynamic Programming for Selective Maintenance in Series-Parallel Systems.  Accepted for publication in IEEE Transactions on ReliabilityPDF
  2. Baycik, N. O., and K. M. Sullivan.  Robust Location of Transparent Interdictions on a Shortest Path Network.  Accepted for publication in IISE Transactions.  PDF
  3. Ruiz, C., M. Heydari, K. M. Sullivan, H. Liao, and E. A. Pohl.  Data Analysis and Resource Allocation in Bayesian Selective Accelerated Reliability Growth.  Accepted for publication in IISE Transactions.
  4. Ruiz, C., H. Liao, E. A. Pohl, and K. M. Sullivan.  A Bayesian Framework for Accelerated Reliability Growth Testing with Multiple Sources of Uncertainty.  Quality and Reliability Engineering International, 35(3): 837-853, 2019.
  5. Ahadi, K., K. M. Sullivan, and K. N. Mitchell.  Budgeting Maintenance Dredging Projects Under Uncertainty to Improve the Inland Waterway Network Performance. Transportation Research Part E: Logistics and Transportation Review, 119: 63-87, 2018.
  6. Margolis, J. T., K. M. Sullivan, S. J. Mason., and M. Magagnotti.  A Multi-Objective Optimization Model for Designing Resilient Supply Chain Networks. International Journal of Production Economics, 204: 174-185, 2018.
  7. Heydari, M., and K. M. Sullivan.  Robust Allocation of Testing Resources in Reliability Growth.  Accepted for publication in Reliability Engineering & System Safety.  PDF
  8. Heydari, M., and K. M. Sullivan.  An Integrated Approach to Redundancy Allocation and Test Planning for Reliability Growth.  Computers & Operations Research, 92, 182-193, 2018.
  9. Sullivan, K. M., D. T. Abdul-Malak, J. P. Kharoufeh, and R. O. Baldwin.  Optimally Locating Application Virtualization Resources on a Network.  Military Operations Research, 20(1): 5-20, 2015.
  10. Sullivan, K. M. and J. C. Smith.  Exact Algorithms for Solving a Euclidean Maximum Flow Network Interdiction Problem. Networks, 64(2): 109-124, 2014.  (Winner of the 2014 Glover-Klingman Prize awarded to the best paper published in Networks.)
  11. Sullivan, K. M., D. P. Morton, F. Pan, and J. C. Smith.  Securing a Border Under Asymmetric Information.  Naval Research Logistics, 61(2): 91-100, 2014.
  12. Sullivan, K. M., J. C. Smith, and D. P. Morton. Convex Hull Representation of the Deterministic Bipartite Network Interdiction Problem. Mathematical Programming, 145(1-2): 349-376, 2014.

Papers in Refereed Conference Proceedings

  1. Sullivan, K. M. and C. R. Cassady.  The CMS+ System for Ranking College Football Teams.  Proceedings of the 2009 Industrial Engineering Research Conference.
  2. Heydari, M., K. M. Sullivan and E. A. Pohl.  Optimal Allocation of Testing Resources in Reliability Growth.  Proceedings of the 2014 Industrial and Systems Engineering Research Conference.
  3. Ruiz, C., H. Liao, E. A. Pohl, and K. M. Sullivan.  Bayesian Accelerated Reliability Growth for Complex Systems.  Accepted to IEEE 2018 Reliability and Maintainability Symposium.

 

  1. 2018 CAREER Award, National Science Foundation
  2. 2014 Glover-Klingman Prize, best paper published in Networks