Articles with public access mandates - James LuedtkeLearn more
Not available anywhere: 1
Service network design with equilibrium-driven demands
M Hamzeei, J Luedtke
IISE Transactions 50 (11), 959-969, 2018
Mandates: US National Science Foundation, US Department of Energy
Available somewhere: 29
Decomposition Algorithms for Two-Stage Chance-Constrained Programs
X Liu, S Küçükyavuz, J Luedtke
Mathematical Programming, 2014
Mandates: US Department of Energy
Strengthened Benders cuts for stochastic integer programs with continuous recourse
M Bodur, S Dash, O Gunluk, J Luedtke
INFORMS Journal on Computing 29 (1), 77-91, 2017
Mandates: US National Science Foundation, US Department of Defense
Mixed-integer rounding enhanced benders decomposition for multiclass service system staffing and scheduling with arrival rate uncertainty
M Bodur, J Luedtke
Management Science, 2016
Mandates: US National Science Foundation
A cycle-based formulation and valid inequalities for DC power transmission problems with switching
B Kocuk, H Jeon, SS Dey, J Linderoth, J Luedtke, A Sun
Operations Research, 2016
Mandates: US National Science Foundation, US Department of Energy
Nonanticipative duality, relaxations, and formulations for chance-constrained stochastic programs
S Ahmed, J Luedtke, Y Song, W Xie
Mathematical Programming, 2016
Mandates: US National Science Foundation, US Department of Energy
Lift-and-project cuts for convex mixed integer nonlinear programs: Linear programming based separation and extended formulations
MR Kılınç, J Linderoth, J Luedtke
Mathematical Programming Computation 9, 499-526, 2017
Mandates: US National Science Foundation, US Department of Energy
Combining progressive hedging with a frank-wolfe method to compute lagrangian dual bounds in stochastic mixed-integer programming
N Boland, J Christiansen, B Dandurand, A Eberhard, J Linderoth, ...
SIAM Journal on Optimization, 2017
Mandates: US National Science Foundation, US Department of Energy, Australian Research …
Solving chance-constrained problems via a smooth sample-based nonlinear approximation
A Peña-Ordieres, JR Luedtke, A Wächter
SIAM Journal on Optimization 30 (3), 2221-2250, 2020
Mandates: US National Science Foundation, US Department of Energy
Exact algorithms for the chance-constrained vehicle routing problem
T Dinh, R Fukasawa, J Luedtke
Mathematical Programming 172 (1), 105-138, 2018
Mandates: US National Science Foundation, US Department of Defense, Natural Sciences …
An Adaptive Partition-based Approach for Solving Two-stage Stochastic Programs with Fixed Recourse
Y Song, J Luedtke
SIAM Journal on Optimization 25 (3), 1344-1367, 2014
Mandates: US Department of Energy
Minotaur: A mixed-integer nonlinear optimization toolkit
A Mahajan, S Leyffer, J Linderoth, J Luedtke, T Munson
Mathematical Programming Computation 13, 301-338, 2021
Mandates: US Department of Energy
Two-stage linear decision rules for multi-stage stochastic programming
M Bodur, J Luedtke
Mathematical Programming 191, 347-380, 2022
Mandates: US National Science Foundation, US Department of Energy, Natural Sciences …
A budgeted maximum multiple coverage model for cybersecurity planning and management
K Zheng, LA Albert, JR Luedtke, E Towle
IISE Transactions 51 (12), 1303-1317, 2019
Mandates: US National Science Foundation
Strong convex nonlinear relaxations of the pooling problem
J Luedtke, C d'Ambrosio, J Linderoth, J Schweiger
SIAM Journal on Optimization 30 (2), 1582-1609, 2020
Mandates: US Department of Energy, German Research Foundation, Federal Ministry of …
Call center arrivals: When to jointly forecast multiple streams?
H Ye, J Luedtke, H Shen
Production and Operations Management 28 (1), 27-42, 2019
Mandates: US National Science Foundation, US Department of Energy
A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs
R Kannan, JR Luedtke
Mathematical Programming Computation 13 (4), 705-751, 2021
Mandates: US Department of Energy
Stochastic DC optimal power flow with reserve saturation
R Kannan, JR Luedtke, LA Roald
Electric Power Systems Research 189, 106566, 2020
Mandates: US Department of Energy
On sample average approximation for two-stage stochastic programs without relatively complete recourse
R Chen, J Luedtke
Mathematical Programming 196 (1), 719-754, 2022
Mandates: US National Science Foundation
New solution approaches for the maximum-reliability stochastic network interdiction problem
E Towle, J Luedtke
Computational Management Science 15 (3), 455-477, 2018
Mandates: US National Science Foundation
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