James R. Luedtke

发表

Integer Programming Approaches for Some Non-convex and Stochastic Optimization Problems

James R. Luedtke, 2007 .

A Sample Approximation Approach for Optimization with Probabilistic Constraints

James R. Luedtke, Shabbir Ahmed, Shabbir Ahmed, 2008, SIAM J. Optim..

Solving Chance-Constrained Problems via a Smooth Sample-Based Nonlinear Approximation

James R. Luedtke, Andreas Wächter, Alejandra Peña-Ordieres, 2019, SIAM J. Optim..

Branch-and-cut approaches for chance-constrained formulations of reliable network design problems

James R. Luedtke, Yongjia Song, Yongjia Song, 2013, Mathematical Programming Computation.

Residuals-based distributionally robust optimization with covariate information.

James R. Luedtke, Rohit Kannan, Guzin Bayraksan, 2020 .

Nonanticipative duality, relaxations, and formulations for chance-constrained stochastic programs

James R. Luedtke, Shabbir Ahmed, Weijun Xie, 2016, Mathematical Programming.

Erratum to: Threshold Boolean form for joint probabilistic constraints with random technology matrix

Alexander Kogan, James R. Luedtke, Miguel A. Lejeune, 2016, Math. Program..

Strategic Planning with Start-Time Dependent Variable Costs

George L. Nemhauser, James R. Luedtke, 2009, Oper. Res..

A Cycle-Based Formulation and Valid Inequalities for DC Power Transmission Problems with Switching

James R. Luedtke, Jeff T. Linderoth, Hyemin Jeon, 2014, Oper. Res..

Some results on the strength of relaxations of multilinear functions

James R. Luedtke, Jeff T. Linderoth, Mahdi Namazifar, 2012, Math. Program..

An integer programming approach for linear programs with probabilistic constraints

George L. Nemhauser, James R. Luedtke, Shabbir Ahmed, 2007, Math. Program..

Mixed-Integer Rounding Enhanced Benders Decomposition for Multiclass Service-System Staffing and Scheduling with Arrival Rate Uncertainty

James R. Luedtke, Merve Bodur, Merve Bodur, 2017, Manag. Sci..

Linearization-based algorithms for mixed-integer nonlinear programs with convex continuous relaxation

James R. Luedtke, Mahdi Hamzeei, Mahdi Hamzeei, 2014, Journal of Global Optimization.

Decomposition algorithms for two-stage chance-constrained programs

Xiao Liu, James R. Luedtke, Simge Küçükyavuz, 2014, Mathematical Programming.

Valid inequalities for separable concave constraints with indicator variables

James R. Luedtke, Jeff T. Linderoth, Cong Han Lim, 2016, IPCO.

Models and solution techniques for production planning problems with increasing byproducts

James R. Luedtke, Jeff T. Linderoth, Srikrishna Sridhar, 2014, J. Glob. Optim..

An integer programming approach for linear programs with probabilistic constraints

George L. Nemhauser, James R. Luedtke, Shabbir Ahmed, 2010, Math. Program..

An Adaptive Partition-Based Approach for Solving Two-Stage Stochastic Programs with Fixed Recourse

James R. Luedtke, Yongjia Song, Yongjia Song, 2015, SIAM J. Optim..

Strong-branching inequalities for convex mixed integer nonlinear programs

James R. Luedtke, Jeff T. Linderoth, Andrew Miller, 2014, Comput. Optim. Appl..

Combining Progressive Hedging with a Frank-Wolfe Method to Compute Lagrangian Dual Bounds in Stochastic Mixed-Integer Programming

Andrew C. Eberhard, James R. Luedtke, Natashia Boland, 2017, SIAM J. Optim..

Chance-Constrained Binary Packing Problems

James R. Luedtke, Yongjia Song, Simge Küçükyavuz, 2014, INFORMS J. Comput..

Lift-and-project cuts for convex mixed integer nonlinear programs

James R. Luedtke, Jeff T. Linderoth, Mustafa R. Kilinç, 2017, Math. Program. Comput..

Lagrangian Dual Decision Rules for Multistage Stochastic Mixed Integer Programming

James R. Luedtke, Maryam Daryalal, Merve Bodur, 2020 .

Computing and maximizing the exact reliability of wireless backhaul networks

David Coudert, James R. Luedtke, Eduardo Moreno, 2018, Electron. Notes Discret. Math..

Valid Inequalities for the Pooling Problem with Binary Variables

James R. Luedtke, Jeff T. Linderoth, Claudia D'Ambrosio, 2011, IPCO.

A branch-and-cut decomposition algorithm for solving chance-constrained mathematical programs with finite support

James R. Luedtke, 2013, Mathematical Programming.

New Formulations for Optimization under Stochastic Dominance Constraints

James R. Luedtke, 2008, SIAM J. Optim..

Exact algorithms for the chance-constrained vehicle routing problem

James R. Luedtke, Ricardo Fukasawa, Thai Dinh, 2018, Math. Program..

Integer programming formulations for minimum deficiency interval coloring

James R. Luedtke, Merve Bodur, 2018, Networks.

Valid inequalities for separable concave constraints with indicator variables

James R. Luedtke, Jeff T. Linderoth, Cong Han Lim, 2018, Math. Program..

An Integer Programming and Decomposition Approach to General Chance-Constrained Mathematical Programs

James R. Luedtke, 2010, IPCO.

Exact algorithms for the chance-constrained vehicle routing problem

James R. Luedtke, Ricardo Fukasawa, Thai Dinh, 2016, IPCO.

Strengthened Benders Cuts for Stochastic Integer Programs with Continuous Recourse

Sanjeeb Dash, Oktay Günlük, James R. Luedtke, 2017, INFORMS J. Comput..

Staffing Call Centers with Uncertain Demand Forecasts: A Chance-Constrained Optimization Approach

Itay Gurvich, James R. Luedtke, Tolga Tezcan, 2010, Manag. Sci..

Locally ideal formulations for piecewise linear functions with indicator variables

James R. Luedtke, Jeff T. Linderoth, Srikrishna Sridhar, 2013, Oper. Res. Lett..

New solution approaches for the maximum-reliability stochastic network interdiction problem

James R. Luedtke, Eli Towle, 2018, Comput. Manag. Sci..

The value of asset visibility in the supply chain single and dual source models

Chelsea C. White, James R. Luedtke, 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs

James R. Luedtke, Rohit Kannan, 2021, Math. Program. Comput..

Data-Driven Sample Average Approximation with Covariate Information

James R. Luedtke, R. Kannan, G. Bayraksan, 2022, 2207.13554.

Mixed-integer nonlinear optimization*†

Christian Kirches, Sven Leyffer, James R. Luedtke, 2013, Acta Numerica.

Effective separation of disjunctive cuts for convex mixed integer nonlinear programs

James R. Luedtke, Jeff T. Linderoth, M. Kilinç, 2010 .

Models and formulations for multivariate dominance-constrained stochastic programs

James R. Luedtke, B. Armbruster, 2015 .

Stochastic DC optimal power flow with reserve saturation

James R. Luedtke, Rohit Kannan, Line A. Roald, 2019, Electric Power Systems Research.

A Dual Approximate Dynamic Programming Approach to Multi-stage Stochastic Unit Commitment

James R. Luedtke, J. Ramakrishnan, 2018, 1801.02259.

Approximating the Lagrangian Dual of a Stochastic Integer Program via Fenchel Cuts

James R. Luedtke, Rui Chen, 2020 .

Electronic Companion to : A Branch-and-Cut Decomposition Algorithm for Solving Chance-Constrained Mathematical Programs

James R. Luedtke, James Luedtke, 2012 .

Residuals-based distributionally robust optimization with covariate information

James R. Luedtke, R. Kannan, G. Bayraksan, 2020, Mathematical Programming.

Sparse Multi-term Disjunctive Cuts for the Epigraph of a Function of Binary Variables

James R. Luedtke, Rui Chen, 2021, IPCO.

2 Preliminaries 2 . 1 A comparison of multivariate stochastic dominance relations

James R. Luedtke, B. Armbruster, 2011 .

Exact algorithms for the chance-constrained vehicle routing problem

James R. Luedtke, Ricardo Fukasawa, Thai Dinh, 2017, Mathematical Programming.

Valid inequalities for separable concave constraints with indicator variables

James R. Luedtke, Jeff T. Linderoth, Cong Han Lim, 2017, Mathematical Programming.

Linearization-based algorithms for mixed-integer nonlinear programs with convex continuous relaxation

James R. Luedtke, Mahdi Hamzeei, Mahdi Hamzeei, 2014, Journal of Global Optimization.

A branch-and-cut decomposition algorithm for solving chance-constrained mathematical programs with finite support

James R. Luedtke, 2013, Mathematical Programming.

Two-stage linear decision rules for multi-stage stochastic programming

James R. Luedtke, Merve Bodur, 2018, Mathematical Programming.

Strong-branching inequalities for convex mixed integer nonlinear programs

James R. Luedtke, Jeff T. Linderoth, Mustafa R. Kilinç, 2014, Computational Optimization and Applications.

A stochastic approximation method for chance-constrained nonlinear programs

James R. Luedtke, R. Kannan, 2018, 1812.07066.

Strong Convex Nonlinear Relaxations of the Pooling Problem

James R. Luedtke, Jeff T. Linderoth, Jeff Linderoth, 2018, SIAM J. Optim..

Minotaur: a mixed-integer nonlinear optimization toolkit

Sven Leyffer, Jeff Linderoth, James R. Luedtke, 2021, Math. Program. Comput..

Parallelizing Subgradient Methods for the Lagrangian Dual in Stochastic Mixed-Integer Programming

Stephen J. Wright, Jeff Linderoth, James R. Luedtke, 2021 .

On sample average approximation for two-stage stochastic programs without relatively complete recourse

James R. Luedtke, Rui Chen, James Luedtke, 2019, Mathematical Programming.

Two-stage linear decision rules for multi-stage stochastic programming

James R. Luedtke, Merve Bodur, 2017, Math. Program..

Applications and algorithms for mixed integer nonlinear programming

Sven Leyffer, Jeff Linderoth, James R. Luedtke, 2009 .

Mixed-integer linear programming for scheduling unconventional oil field development

James R. Luedtke, Jeff T. Linderoth, Jeff Linderoth, 2020 .

A budgeted maximum multiple coverage model for cybersecurity planning and management

James R. Luedtke, Laura A. Albert, James Luedtke, 2019, IISE Trans..

Heteroscedasticity-aware residuals-based contextual stochastic optimization

James R. Luedtke, James Luedtke, Rohit Kannan, 2021, 2101.03139.

A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs

James R. Luedtke, James Luedtke, Rohit Kannan, 2018, Mathematical Programming Computation.

Lagrangian Dual Decision Rules for Multistage Stochastic Mixed-Integer Programming

James R. Luedtke, Merve Bodur, Maryam Daryalal, 2020, Operations Research.

Special Issue: Global Solution of Integer, Stochastic and Nonconvex Optimization Problems

James R. Luedtke, Santanu S. Dey, N. Sahinidis, 2022, Mathematical Programming.

Intersection Disjunctions for Reverse Convex Sets

James R. Luedtke, James Luedtke, Eli Towle, 2019, Math. Oper. Res..