Design of methods for solving discrete and stochastic optimization problems.
Years at WID2010 - present
- B.S., Industrial Engineering, University of Wisconsin-Madison
- M.S., Operations Research, Georgia Institute of Technology
- Ph.D., Industrial and Systems Engineering, Georgia Institute of Technology
- Postdoctoral Research, IBM T.J. Watson Research Center
Stochastic and mixed-integer programming, with applications in areas such as energy planning, service systems staffing, and supply chain management.
- J. Luedtke. “An Integer Programming and Decomposition Approach to General Chance-Constrained Mathematical Programs,” The 14th Conference for Integer Programming and Combinatorial Optimization (IPCO 2010), Proceedings. Lecture Notes in Computer Science, 271-284.
- B. Armbruster and J. Luedtke. “Models and Formulations for Multivariate Dominance Constrained Stochastic Programs,” Submitted for publication, 2010.
- I. Gurvich, J. Luedtke, and T. Tezcan. “Staffing Call Centers With Uncertain Demand Forecasts: A Chance-Constrained Optimization Approach,” Management Science, To appear, 2010.
- J. Luedtke. “New Formulations for Optimization Under Stochastic Dominance Constraints,” SIAM Journal on Optimization, 2008.
- J. Luedtke and S. Ahmed. “A Sample Approximation Approach for Optimization with Probabilistic Constraints,” SIAM Journal on Optimization, 19, 674-699 (2008).
- J. Luedtke, S. Ahmed and G. Nemhauser. “An Integer Programming Approach for Linear Programs with Probabilistic Constraints,” Mathematical Programming, 122, 247-272 (2010).
- J. Luedtke, S. Ahmed and G. Nemhauser. “An Integer Programming Approach for Linear Programs with Probabilistic Constraints,” The Twelfth Conference for Integer Programming and Combinatorial Optimization (IPCO 2007), Proceedings. Lecture Notes in Computer Science 4513 Spring 2007.
- J. Luedtke and G. Nemhauser. “Strategic Planning with Start-Time Dependent Variable Costs,” Operations Research, 57, 1250-1261 (2009).
- J. Luedtke and C.C. White, III. “The Value of Asset Visibility in the Supply Chain: Single and Dual Source Models,” 2004 IEEE Conference on Systems, Man and Cybernetics: Proceedings, Vol. 5, 4189-94.