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Mathematics

D-Index
32
Citations
5960
World Ranking
3137
National Ranking
1257

Overview

Jeff Linderoth is affiliated with the University of Wisconsin-Madison in the United States. Their research focuses primarily on fields related to Engineering and Computer Science, with significant contributions to Industrial and Manufacturing Engineering, Control and Systems Engineering, Computational Theory and Mathematics, Numerical Analysis, and Management Science and Operations Research.

Their work covers a range of topics including:

  • Optimization and Packing Problems
  • Advanced Optimization Algorithms Research
  • Advanced Control Systems Optimization
  • Formal Methods in Verification
  • Manufacturing Process and Optimization
  • Optimization and Search Problems
  • Advanced Manufacturing and Logistics Optimization

Linderoth has published extensively in several academic venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • INFORMS Journal on Optimization
  • Mathematical Programming Computation
  • Optimization and Engineering
  • SIAM Journal on Optimization

Some of the recent papers published by Jeff Linderoth are:

  • "MIPLIB 2017: data-driven compilation of the 6th mixed-integer programming library," 2021, Mathematical Programming Computation
  • "The hierarchical organization of autocatalytic reaction networks and its relevance to the origin of life," 2022, PLoS Computational Biology
  • "Minotaur: a mixed-integer nonlinear optimization toolkit," 2020, Mathematical Programming Computation
  • "Optimization-based dispatching policies for open-pit mining," 2021, Optimization and Engineering
  • "Strong Convex Nonlinear Relaxations of the Pooling Problem," 2020, SIAM Journal on Optimization

Linderoth frequently collaborates with a set of coauthors, including:

  • Alberto Del Pia
  • James Luedtke
  • Haoran Zhu
  • Akhilesh Soni

Their interdisciplinary expertise and collaborative work span multiple areas of optimization and applied mathematics, contributing to both theoretical advancements and practical applications in engineering and computational optimization.

Best Publications

  • Mixed-integer nonlinear optimization

    Pietro Belotti;Christian Kirches;Sven Leyffer;Jeff T. Linderoth

  • A Computational Study of Search Strategies for Mixed Integer Programming

    J. T. Linderoth;M. W. P. Savelsbergh

  • The empirical behavior of sampling methods for stochastic programming

    Jeff T. Linderoth;Alexander Shapiro;Stephen J. Wright

  • An enabling framework for master-worker applications on the Computational Grid

    J.-P. Goux;S. Kulkarni;J. Linderoth;M. Yoder

  • Algorithms and Software for Convex Mixed Integer Nonlinear Programs

    Pierre Bonami;Mustafa Kilinç;Jeff Linderoth

  • Solving large quadratic assignment problems on computational grids

    Kurt Anstreicher;Nathan Brixius;Jean-Pierre Goux;Jeff Linderoth

  • Decomposition Algorithms for Stochastic Programming on a Computational Grid

    Jeff Linderoth;Stephen Wright

  • Perspective reformulations of mixed integer nonlinear programs with indicator variables

    Oktay Günlük;Jeff Linderoth

  • Orbital Branching

    James Ostrowski;Jeff Linderoth;Fabrizio Rossi;Stefano Smriglio

  • A simplicial branch-and-bound algorithm for solving quadratically constrained quadratic programs

    Jeff Linderoth

  • FilMINT: An Outer Approximation-Based Solver for Convex Mixed-Integer Nonlinear Programs

    Kumar Abhishek;Sven Leyffer;Jeff Linderoth

  • MIPLIB 2017: data-driven compilation of the 6th mixed-integer programming library

    Ambros M. Gleixner;Gregor Hendel;Gerald Gamrath;Tobias Achterberg

  • Orbital branching

    James Ostrowski;Jeff Linderoth;Fabrizio Rossi;Stefano Smriglio

  • Noncommercial Software for Mixed-Integer Linear Programming

    Jeffrey T. Linderoth;Ted K. Ralphs

  • Reformulation and sampling to solve a stochastic network interdiction problem

    Udom Janjarassuk;Jeff Linderoth

  • FilMINT: An Outer-Approximation-Based Solver for Nonlinear Mixed Integer Programs

    Kumar Abhishek;Sven Leyffer;Jeffrey T. Linderoth

  • Perspective Reformulation and Applications

    Oktay Günlük;Jeff Linderoth

  • Some results on the strength of relaxations of multilinear functions

    James R. Luedtke;Mahdi Namazifar;Jeff T. Linderoth

  • The Mathematical Foundations of Epistemic Network Analysis.

    Dale Bowman;Zachari Swiecki;Zhiqiang Cai;Yeyu Wang

  • Master–Worker: An Enabling Framework for Applications on the Computational Grid

    Jean-Pierre Goux;Sanjeev Kulkarni;Michael Yoder;Jeff Linderoth

  • GRIP: scalable 3D global routing using integer programming

    Tai-Hsuan Wu;Azadeh Davoodi;Jeffrey T. Linderoth

  • Perspective relaxation of mixed integer nonlinear programs with indicator variables

    Oktay Günlük;Jeff Linderoth

  • MILP Software

    Unknown

  • Functional description of MINTO, a Mixed INTeger Optimizer Version 3.1

    George L. Nemhauser;Jeff T. Linderoth

Frequent Co-Authors

Sven Leyffer
Sven Leyffer Argonne National Laboratory
Stephen J. Wright
Stephen J. Wright University of Wisconsin–Madison
James Ostrowski
James Ostrowski Blue River Technology
Martin W. P. Savelsbergh
Martin W. P. Savelsbergh Georgia Institute of Technology
David Williamson Shaffer
David Williamson Shaffer University of Wisconsin–Madison
Santanu S. Dey
Santanu S. Dey Georgia Institute of Technology
Natashia Boland
Natashia Boland Georgia Institute of Technology
Russell Bent
Russell Bent Los Alamos National Laboratory
Ben Liblit
Ben Liblit University of Wisconsin–Madison
Ian A. Hiskens
Ian A. Hiskens University of Michigan–Ann Arbor

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