M. Kilinc, J.T. Linderoth, J. Luedtke, A. Miller, “Strong branching
inequalities for mixed integer nonlinear programs," Computational
Optimization & Applications, accepted for publication (2014).
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).
M. Hamzeei and J. Luedtke, "Linearization-based algorithms for
mixed-integer nonlinear programs with convex continuous relaxation", Journal
of Global Optimization, 59:343-635 (2014).
Y. Song, S. Kucukyavuz, and J. Luedtke, "Chance-constrained binary
packing problems," INFORMS Journal on Computing,
articles in advance (2014).
J. Luedtke, "A branch-and-cut decomposition algorithm for solving
chance-constrained mathematical programs with finite support",
Mathematical Programming, 146:219-244 (2014).
B. Armbruster and J. Luedtke, "Models and formulations for multivariate
dominance constrained stochastic programs," IIE Transactions, Online
First (2014).
S. Sridhar, J. Linderoth, and J. Luedtke, "Locally ideal formulations for
piecewise linear functions with indicator variables",
Operations Research Letters, 41:627-632 (2013).
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).
P. Belotti, C. Kirches, S. Leyffer, J. Linderoth, J. Luedtke, and A.
Mahajan, "Mixed-integer nonlinear optimization,"
Acta Numerica, 22:1-131 (2013).
J. Luedtke, M. Namazifar, and J. Linderoth, “Some results on the strength
of relaxations of multilinear functions,”
Mathematical Programming, 136:325-351 (2012).
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).
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 and G. Nemhauser, "Strategic planning with start-time
dependent variable costs," Operations Research, 57:1250-1262 (2009).
J. Luedtke, "New formulations for optimization under stochastic
dominance constraints," SIAM Journal on Optimization, 19:1433-1450
(2008).
J. Luedtke and S. Ahmed, "A sample approximation approach for
optimization with probabilistic constraints," SIAM Journal on
Optimization, 19:674-699 (2008).
Conference Papers:
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).
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. 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).
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).
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).
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).
Selected Submitted and Working Papers:
S. Ahmed, J. Luedtke, Y. Song, and W. Xie, “Nonanticipative duality and
mixed-integer programming formulations for chance-constrained stochastic
programs,” (2014).
X. Liu, S. Küçükyavuz and J. Luedtke, “Decomposition algorithms for two-stage
chance-constrained programs,” (2014).
M. Bodur and J. Luedtke, “Integrated service system staffing and scheduling via
stochastic integer programming,” (2014).
Y. Song and J. Luedtke, “An adaptive partition-based approach for solving
two-stage stochastic programs with fixed recourse”, (2014).
M. Bodur, S. Dash, O. Günlük, and J. Luedtke, “Strengthened Benders cuts for
stochastic integer programs with continuous recourse,” (2014).
H. Ye, J. Luedtke, and H. Shen, “Forecasting and staffing call centers
with multiple uncertain arrival streams,” (2012).
M. Kilinc, J. Linderoth, and J. Luedtke, “Effective separation of
disjunctive cuts for convex mixed integer nonlinear programs,” (2012).
Other Publications:
J. Luedtke. "Integer Programming Approaches for Some Non-convex and
Stochastic Optimization Problems", Ph.D. Dissertation,
2007.
Data and online supplements:
Data for paper "An integer programming approach
for linear programs with probabilistic constraints," by Luedtke, Ahmed and
Nemhauser, Mathematical Programming, 2008: Download here.
Online supplement for "A branch-and-cut algorithm for solving
chance-constrained mathematical programs" (2012): Download here.