James Luedtke Professor and Associate Chair for Graduate Studies Department of Industrial and Systems Engineering University of Wisconsin-Madison Madison, WI 53706 jim.luedtke at wisc dot edu

Education:

• Ph.D., Industrial and Systems Engineering, Georgia Institute of Technology, 2007.
• M.S., Operations Research, Georgia Institute of Technology, 2004.
• B.S., Industrial Engineering, University of Wisconsin-Madison, 2001.

Research Interests:

• Mixed-integer linear and nonlinear optimization
• Stochastic optimization
• Applications of optimization

Journal Papers:

1. A. Peña-Ordieres, J. Luedtke, and A. Waechter, "Solving chance-constrained problems via a smooth sample-based nonlinear approximation," SIAM Journal on Optimization, to appear (2020). Preprint.
2. A. Soni, J. Linderoth, J. Luedtke, and F. Rigterink, "Mixed-integer linear programming for scheduling unconventional oil field development," Optimization and Engineering, (2020). Preprint.
3. C.H. Lim, J. Linderoth, J. Luedtke, and S. Wright, "Parallelizing subgradient methods for the Lagrangian dual in stochastic mixed-integer programming," INFORMS Journal on Optimization, to appear (2020). Preprint.
4. J. Luedtke, C. D'Ambrosio, J. Linderoth, and J. Schweiger, "Strong convex nonlinear relaxations of the pooling problem," SIAM Journal on Optimization, 30:1582-1609, (2020). Preprint.
5. K. Zhang, L. Albert, J. Luedtke, and E. Towle, "A budgeted maximum multiple coverage model for cybersecurity planning and management," IISE Transactions, 51:1303-1317 (2019) Preprint.
6. H. Ye, J. Luedtke, and H. Shen, "Call Center Arrivals: When to Jointly Forecast Multiple Streams?," Production and Operations Management, 28:27-42 (2019).
7. M. Bodur and J. Luedtke, “Two-stage linear decision rules for multi-stage stochastic programming," Mathematical Programming (2018). Preprint.
8. E. Towle and J. Luedtke, "New solution approaches for the maximum-reliability stochastic network interdiction problem," Computational Management Science, 15:455-477 (2018). Preprint.
9. M. Hamzeei and J. Luedtke, "Service network design with equilibrium-driven demands," IISE Transactions, 50:959-969 (2018).
10. M. Bodur and J. Luedtke, “Integer programming formulations for minimum deficiency interval coloring", Networks, 72:249-271 (2018).
11. A. Eberhard, N. Boland, J. Christiansen, B. Dandurand, J. Linderoth, J. Luedtke, and F. Oliveira, “Combining progressive hedging with a Frank-Wolfe method to compute Lagrangian dual bounds in stochastic mixed-integer programming,” SIAM Journal on Optimization , 28:1312-1336 (2018) .
12. C.H. Lim, J. Linderoth, and J. Luedtke, “Valid inequalities for separable concave constraints with indicator variables,” Mathematical Programming , 172:415-442 (2018).
13. T. Dinh, R. Fukasawa, and J. Luedtke, “Exact algorithms for the chance-constrained vehicle routing problem,” Mathematical Programming , 172:105-138 (2018).
14. M. Kilinc, J. Linderoth, and J. Luedtke, “Lift-and-Project Cuts for Convex Mixed Integer Nonlinear Programs Linear Programming Based Separation and Extended Formulations,” Mathematical Programming Computation, 9:499-526 (2017). ( Preprint of earlier version)
15. S. Ahmed, J. Luedtke, Y. Song, and W. Xie, “Nonanticipative duality, relaxations, and formulations for chance-constrained stochastic programs,” Mathematical Programming, 162:51-81 (2017).
16. M. Bodur, S. Dash, O. Günlük, and J. Luedtke, “Strengthened Benders cuts for stochastic integer programs with continuous recourse,” INFORMS Journal on Computing, 29:77-91 (2017).
17. M. Bodur and J. Luedtke, “Mixed-integer rounding enhanced benders decomposition for multiclass service system staffing and scheduling with arrival rate uncertainty,” Management Science, 63:2073-2091 (2017). Preprint.
18. B. Kocuk, H. Jeon, S.S. Dey, J. Linderoth, J. Luedtke, and X. Sun, "A cycle-based formulation and valid inequalities for DC power transmission with switching,” Operations Research, 64(4):922-938, (2016).
19. X. Liu, S. Küçükyavuz and J. Luedtke, “Decomposition algorithms for two-stage chance-constrained programs,” Mathematical Programming, 157:219-243 (2016).
20. Y. Song and J. Luedtke, "An adaptive partition-based approach for solving two-stage stochastic programs with fixed recourse," SIAM Journal on Optimization, 25:1344-1367 (2015).
21. M. Kilinc, J.T. Linderoth, J. Luedtke, A. Miller, “Strong branching inequalities for mixed integer nonlinear programs," Computational Optimization & Applications, 59:639-665 (2014).
22. S. Sridhar, J. Linderoth, and J. Luedtke, "Models and solution techniques for production planning problems with increasing byproducts," Journal of Global Optimization, 59:597-631 (2014).
23. M. Hamzeei and J. Luedtke, "Linearization-based algorithms for mixed-integer nonlinear programs with convex continuous relaxation," Journal of Global Optimization, 59:343-365 (2014).
24. Y. Song, S. Kucukyavuz, and J. Luedtke, "Chance-constrained binary packing problems," INFORMS Journal on Computing, 26:735-747 (2014).
25. J. Luedtke, "A branch-and-cut decomposition algorithm for solving chance-constrained mathematical programs with finite support," Mathematical Programming, 146:219-244 (2014).
26. B. Armbruster and J. Luedtke, "Models and formulations for multivariate dominance constrained stochastic programs," IIE Transactions, 47:1-14 (2014).
27. S. Sridhar, J. Linderoth, and J. Luedtke, ""Locally ideal formulations for piecewise linear functions with indicator variables," Operations Research Letters, 41:627-632 (2013).
28. Y. Song and J. Luedtke. “Branch-and-cut approaches for chance-constrained formulations of reliable network design problems,” Mathematical Programing Computation 5:397-432 (2013).
29. P. Belotti, C. Kirches, S. Leyffer, J. Linderoth, J. Luedtke, and A. Mahajan, "Mixed-integer nonlinear optimization," Acta Numerica, 22:1-131 (2013).
30. J. Luedtke, M. Namazifar, and J. Linderoth, “Some results on the strength of relaxations of multilinear functions,” Mathematical Programming, 136:325-351 (2012).
31. I. Gurvich, J. Luedtke, and T. Tezcan, “Staffing call-centers with uncertain demand forecasts: a chance-constrained optimization approach,” Management Science, 56:1093-1115 (2010).
32. J. Luedtke, S. Ahmed and G. Nemhauser, "An integer programming approach for linear programs with probabilistic constraints," Mathematical Programming, 122:247-272 (2010).
33. J. Luedtke and G. Nemhauser, "Strategic planning with start-time dependent variable costs," Operations Research, 57:1250-1262 (2009).
34. J. Luedtke, "New formulations for optimization under stochastic dominance constraints," SIAM Journal on Optimization, 19:1433-1450 (2008).
35. J. Luedtke and S. Ahmed, "A sample approximation approach for optimization with probabilistic constraints," SIAM Journal on Optimization, 19:674-699 (2008).

Refereed Conference Papers:

1. R. Kannan, J. Luedtke, and L. Roald, "Stochastic DC optimal power flow with reserve saturation", XXI Power Systems Control Conference (PSCC), Porto, Portugual (2020) Preprint.
2. D. Coudert, J. Luedtke, E. Moreno, and K. Priftis, "Computing and maximizing the exact reliability of wireless backhaul networks," International Network Optimization Conference (INOC) 2017, Lisbon, Portugal (2017).
3. T. Dinh, R. Fukasawa, and J. Luedtke, “Exact algorithms for the chance-constrained vehicle routing problem,” Integer Programming and Combinatorial Optimization (IPCO) 2016, Liege, Belgium (2016).
4. C.H. Lim, J. Linderoth, and J. Luedtke, “Valid inequalities for separable concave constraints with indicator variables,” Integer Programming and Combinatorial Optimization (IPCO) 2016, Liege, Belgium (2016).
5. C. D’Ambrosio, J. Linderoth, and J. Luedtke, “Valid inequalities for the pooling problem with binary variables,” 117-129, Integer Programming and Combinatorial Optimization (IPCO) 2011, New York, NY (2011).
6. J. Luedtke, “An integer programming and decomposition approach to general chance-constrained mathematical programs,” Integer Programming and Combinatorial Optimization (IPCO) 2010, 271—284, Lausanne, Switzerland (2010).
7. S. Leyffer, J. Linderoth, J. Luedtke, A. Miller and T. Munson, “Applications and algorithms for mixed integer nonlinear programming,” SciDAC 2009, J. of Physics: Conference Series, San Diego, California (2009).
8. 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 (2007).
9. 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, 5:4189-94 (2004).

Submitted Papers and Technical Reports:

• A. Smith, J. Linderoth, and J. Luedtke, "Optimization-based dispatching policies for open pit mining" (2020).
• M. Daryalal, M. Bodur, and J. Luedtke, "Lagrangian dual decision rules for multistage stochastic mixed integer programming" (2020).
• R. Chen and J. Luedtke, "On sample average approximation for two-stage stochastic programs without relatively complete recourse" (2019).
• R. Kannan and J. Luedtke, "A stochastic approximation method for chance-constrained nonlinear programs" (2019).
• E. Towle and J. Luedtke "Intersection disjunctions for reverse convex sets" (2019).
• J. Ramakrishnan and J. Luedtke, "A Dual Approximate Dynamic Programming Approach to Multi-stage Stochastic Unit Commitment" (2018).
• A. Mahajan, S. Leyffer, J. Linderoth, J. Luedtke, and T. Munson, " Minotaur: A Mixed-Integer Nonlinear Optimization Toolkit" (2017).
• A. Kogan, M. Lejeune, and J. Luedtke, "Erratum to: Threshold Boolean form for joint probabilistic constraints with random technology matrix," Mathematical Programming, 155:617-620 (2015).
• J. Luedtke, "A Counterexample to `Threshold Boolean form for joint probabilistic constraints with random technology matrix’,” (2014).
• J. Luedtke, “Optimization with approximate stochastic dominance constraints: Models and formulations," Proceedings of the 2011 NSF Engineering Research and Innovation Conference, Atlanta, GA, January (2011).
• J. Goez, J. Luedtke, D. Rajan, and J. Kalagnanam, "Stochastic unit commitment problem," IBM report RC24713 (W0812-119) (2008).
• J. Luedtke and C.C. White, "Hazmat transportation and security: survey and directions for future research," Department of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA (2002)

Other Publications:

• J. Luedtke. "Integer Programming Approaches for Some Non-convex and Stochastic Optimization Problems," Ph.D. Dissertation, 2007.

Slides:

• "Introduction to Stochastic Optimization", January 2018.

Researh Group:

• Rohit Kannan

• Rui Chen
• Akhilesh Soni (co-advised wit Jeff Linderoth)

• Conghan Lim. Current position: AI Resident, Uber ATG

• Eli Towle, PhD 2019. Current position: Optimization Support Engineer, Gurobi Optimization.
• Amanda Smith, PhD 2018. Current position: Associate Chair for Undergraduate Affiars, Department of Industrial and Systems Engineering, University of Wisconsin-Madison.
• Thai Dinh, MS 2016. Current position: Data scientist, Trusting Social
• Merve Bodur, PhD 2015. Current position: Assistant Professor, Department of Mechanical and Industrial Engineering, University of Toronto.
• Mahdi Hamzeei, PhD 2014. Current position: Senior Data Scientest, Precima.
• Yongjia Song, PhD 2013. Current position: Assistant Professor, Department of Statistical Sciences and Operations Research, Virginia Commonwealth University.

• Mahdi Namazifar, PhD 2013 (co-advised with Jeff Linderoth). Current position: Senior Data Scientist, Twitter Cortex and CUAD.
• Srikrishna Sridhar, PhD 2014 (co-advised with Jeff Linderoth and Stephen Wright). Current position: Engineering Manager, Apple.

Current Research Projects:

• "MACSER: Multifaceted Mathematics for Rare, High-Impact Events in Complex Energy and Environment Systems", UW-Madison Principal Investigator, Department of Energy Office of Science, Advance Scientific Computing Research program. Subcontract through Argonne National Laboratory. With co-PI's M. Ferris, J. Linderoth, L. Roald, S. Wright, V. Zavala. 9/2017 - 8/2018, $600,000 per year (UW-Madison amount).
• “Scalable Methods for Solving Stochastic Mixed-Integer Programs”, National Science Foundation, Principal Investigator, with co-PI’s J. Linderoth and S. Wright, 9/1/2016 – 8/31/2020, $399,563.

Completed Research Projects:

• “Large-scale Stochastic Mixed-Integer Nonlinear Programming," ExxonMobil Upstream Research Corporation, co-Principal Investigator with J. Linderoth (PI) and S. Wright (co-PI). 12/2010 – 12/2019.
• “SBE: Small: An Optimization Framework for Prioritizing Cyber-security Mitigations for Securing Information Technology Infrastructure,” National Science Foundation, (SES-Division of Social and Economic Sciences), co-PI with L. Albert (PI), 8/2014 – 7/2019, $447,828.
• “Multifaceted Mathematics Center for Complex Energy Systems" Department of Energy Office of Science, Advance Scientific Computing Research program. Subcontract through Argonne National Laboratory. With M. Ferris (PI), and co-PI's C. Demarco, B. Lesieutre, J. Linderoth, S. Wright. 9/2012 - 8/2017, $750,000 per year.
• “Strengthened Benders Cuts for Stochastic Integer Programs with Continuous Recourse”, Office of Naval Research, Principal Investigator, 5/1/2015 – 4/30/2017, $90,002.
• “Collaborative Research: Staffing and Routing in Service Systems with Uncertain Arrival Rates: An Integrated Stochastic Programming and Asymptotic Analysis Approach," Principal Investigator in collaboration with T. Tezcan (Simon School of Business, University of Rochester), National Science Foundation (CMMI-SES), 10/2011 - 9/2014, $206,141 (UW portion).
• “CAREER: Risk Management via Stochastic Programming: Models, Computation, and Applications," National Science Foundation (CMMI-OR), Principal Investigator, 2/2010 - 1/2015, $400,000.
• “MINOTAUR: A New Toolkit for Solving Mixed-Integer and Nonlinear Optimization Problems,” Department of Energy (funded via Argonne National Lab subcontract), co-Principal Investigator with J. Linderoth (PI), 10/2011 - 9/2013, $175,878.
• “A Stochastic and Integer Programming Approach to Service Systems Scheduling Under Arrival Rate Uncertainty," University of Wisconsin-Madison Graduate School Research Committee, Principal Investigator, 9/2011 – 8/2012, $34,382.
• “Collaborative Research: Next-Generation Solvers for Mixed-Integer Nonlinear Programs: Structure, Search and Implementation,'' Department of Energy (DE-PS02-08ER08-13), co-Principal Investigator with J. Linderoth (PI), $528,476, 8/08 - 8/12.
• “Collaborative Research: Next-Generation Solvers for Mixed-Integer Nonlinear Programs: Structure, Search and Implementation,'' National Science Foundation (CCF-0830153), co-Principal Investigator with J. Linderoth (PI), $199,997, 1/09 - 1/13.
• “Warehouse Management for Hy-Vee Flow Through System,” Hy-Vee, Inc., co-Principal Investigator with R. Veeramani (PI), 5/2008 – 4/2009, $84,948.

Professional Service:

• Mathematical Optimization Society Council: 2018 - present.
• Guest editor, Mathematical Programming, Series B, 2020 - present.
• SIAM Activity Group on Optimization, Secretary: 2017 - 2019.
• INFORMS Nicholson Paper Prize Committee, 2013 - 2014, 2017.
• Mathematical Optimization Society Publications Committee: 2016 - present. Chair, 2019 - present.
• INFORMS Optimization Society Student Paper Prize Committee Chair: 2016.
• Committee on Stochastic Programming (elected board of Stochastic Programming Society): 2013 - present.
• Secretary/Treasurer of INFORMS Optimization Society: 2011 – 2015.
• Associate editor, SIAM Journal on Optimization, 2016 – present.
• Associate editor, INFORMS Journal on Computing, 2014 – 2018.
• Associate editor, Optimization Letters, 2013 – 2016.
• Associate editor, Journal of Optimization Theory and Applications, 2011 - 2016.
• Associate editor, IIE Transactions, 2011 – 2013.
• Referee for: Mathematical Programming, Operations Research, Management Science, SIAM Review, Mathematics of Operations Research, Manufacturing & Service Operations Management, European Journal of Operational Research, Operations Research Letters, IIE Transactions, INFORMS Journal on Computing, SIAM Journal on Optimization, Annals of Operations Research, Journal of Global Optimization, Optimization Methods & Software, Mathematical Programming Computation, Optimization Letters, Computers and Operations Research, Transportation Science, Journal of Optimization Theory and Applications, Engineering and Optimization.
• Scientific Committee Member, International Conference on Stochastic Programming 2019, Trondheim, Norway, 2019.
• Program Committee Member, Integer Programming and Combinatorial Optimization 2019, University of Michigan, 2019.
• Scientific Committee Member, 23rd International Symposium on Mathematical Programming, Trondheim, Norway, 2019.
• Program Committee Member, International Conference on Stochastic Programming 2016, Busios Brazil, August 2016.
• Integer Programming Track Co-Chair (with Simge Küçükyavuz), 2015 INFORMS Computing Society Conference, Richmond, VA, January 2015.
• Program Committee Chair, 2013 Workshop on Mixed-Integer Programming, University of Wisconsin-Madison, July 2013.
• Program Committee Member, 2012 Workshop on Mixed-Integer Programming, University of California Davis, July 2012.

Data and online supplements:

• Data for "A branch-and-cut decomposition algorithm for solving chance-constrained mathematical programs with finite support," Mathematical Programming, 146:219-244, (2014): Instances with right-hand side randomness. Instances with random constraints.
• Data for right-hand side randomness instancs in "A branch-and-cut decomposition algorithm for solving chance-constrained mathematical programs with finite support," Mathematical Programming, 146:219-244, (2014): Download here.
• Data for paper "An integer programming approach for linear programs with probabilistic constraints," by Luedtke, Ahmed and Nemhauser, Mathematical Programming, 122:247-272 (2010): Download here.
• Online supplement for "A branch-and-cut decomposition algorithm for solving chance-constrained mathematical programs with finite support," Mathematical Programming, 146:219-244, (2014): Download here.

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