Linderoth, Jeffrey T.

B.S. (highest honors) 1992, General Engineering, University of Illinois at Urbana-Champaign
M.S. 1994, Operations Research, Georgia Institute of Technology
Ph.D., 1998, Industrial Engineering, Georgia Institute of Technology

Fields of Interest

Numerical Optimization: Integer programming and Stochastic programming
High Performance and Grid Computing
Applications in Logistics, Finance, and Health-Care

Publications

Selected papers only. For a full list, please see my Extended Homepage
O. Gunluk and J. T. Linderoth, "Perspective Relaxation of Mixed Integer Nonlinear Programs with Indicator Variables", IPCO XIII, to appear, 2008.
J. Ostrowski, J. Linderoth, F. Rossi, and S. Smriglio, "Constraint Orbital Branching," IPCO XIII, to appear, 2008.
W. Glankwamdee, J. Linderoth, J. Shen, P. Connard, and J. Hutton, "Combining Optimization and Simulation for Strategic and Operational Industrial Gas Production and Distribution," Computers and Chemical Engineering, to appear, 2008.
U. Janjarassuk and J. T. Linderoth, "Reformulation and Sampling to Solve a Stochastic Network Interdiction Problem", Networks, to appear, 2008.
James Ostrowski, Jeff Linderoth, Fabrizio Rossi, and Stefano Smirglio, "Orbital Branching", IPCO XII, Lecture Notes in Computer Science, Vol. 4517, pages 104-118, 2007.
J. T. Linderoth, A. Shapiro, and S. J. Wright, The Empirical Behavior of Sampling Methods for Stochastic Programming, Annals of Operations Research, Vol. 142, pp. 219-245, 2006,
J. T. Linderoth, "A Simplicial Branch-and-Bound Algorithm for Solving Quadratically Constrained Quadratic Programs", Mathematical Programming, Series B, Vol. 103, pp. 251-282, 2005.
J. T. Linderoth and S. J. Wright, "Decomposition Algorithms for Stochastic Programming on a Computational Grid," Computational Optimization and Applications, Vol. 24 pp. 207-250, 2003.
K. Anstreicher and N. Brixius and J.-P. Goux and J. T. Linderoth, "Solving Large Quadratic Assignment Problems on Computational Grids," Mathematical Programming, Series B, Vol. 91, pp. 563-588, 2002.
J. T. Linderoth, E. K. Lee, and M. W. P. Savelsbergh, "A Parallel, Linear Programming Based Heuristic for Large Scale Set Partitioning Problems," INFORMS Journal on Computing, Vol. 13, pp. 191-209, 2001.
J.-P Goux, S. Kulkarni, J. T. Linderoth, and M. E. Yoder, ''Master-Worker: An Enabling Framework for Applications on the Computational Grid'', Cluster Computing, Vol. 4, pp. 63-70, 2001.
Q. Chen, M. Ferris, and J. T. Linderoth, "FATCOP 2.0: Advanced Features in an Opportunistic Mixed Integer Programming Solver," Annals of Operations Research Vol. 103, pp. 17-32, 2001.
A. Atamturk, E. L. Johnson, J. T. Linderoth and M. W. P. Savelsbergh, "A Relational Modeling System for Linear and Integer Programming," Operations Research, Vol. 48, pp.846-857, 2000.
J. T. Linderoth and M. W. P. Savelsbergh, "A Computational Study of Branch and Bound Search Strategies for Mixed Integer Programming," INFORMS Journal on Computing, Vol. 11, pp. 173-187, 1999.

Selected Awards, Honors and Societies

Eleanor & Joseph F. Libsch Early Career Research Award, Lehigh University, 2006.
Department of Energy Early Career Principal Investigator Award: Applied Mathematics, Computer Science, and High-Performance Networks, 2005-2007
IBM Faculty Partnership Award, 2005-2006
Lehigh Engineering Ingenuity Award for Exceptional Accomplishment in Teaching and/or Research by a Junior Faculty Member, 2005
Best Paper Award, with S. J. Wright, Computational Optimization and Applications, 2003.
SIAM Activity Group on Optimization Prize, with K. Anstreicher, N. Brixius, and J.-P Goux, 2002
Enrico Fermi Scholar, Argonne National Lab, 1999-2000.

Editorial

Editorial Board, Computation Optimization and Applications, 2007-present
Associate Editor, Asia-Pacific Journal of Operational Research, 2007-present
Associate Editor, INFORMS Journal on Computing, 2003-present.

Summary

Professor Linderoth's research focuses on modeling and solving real-world, large-scale optimization problems. Specific research areas within optimization include integer programming, used for modeling yes/no decisions, and stochastic programming, useful for decision making under uncertainty. His research places a particular emphasis on developing high-performance, distributed optimization algorithms and software. Application domains of interest and experience include financial engineering, logistics-supply chain, and health care.

Copyright 2008 The Board of Regents of the University of Wisconsin System
Date last modified: 04-Feb-2008
Content by: linderoth@wisc.edu
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