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Optimization Methods and Software, 2002
This paper analyzes the algorithmic tools presented in [D. Dentcheva, A. Prekopa and A. Ruszczy ` ski. Bounds for Probabilistic Integer Programming Problems, RUTCOR, Rutgers University, NJ, RRR 31-99; D. Dentcheva, A. Prekopa and A. Ruszczy ` ski (2000). Concavity and efficient points of discrete distributions in probabilistic programming. Mathematical
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This paper analyzes the algorithmic tools presented in [D. Dentcheva, A. Prekopa and A. Ruszczy ` ski. Bounds for Probabilistic Integer Programming Problems, RUTCOR, Rutgers University, NJ, RRR 31-99; D. Dentcheva, A. Prekopa and A. Ruszczy ` ski (2000). Concavity and efficient points of discrete distributions in probabilistic programming. Mathematical
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Rates of Convergence in Stochastic Programs with Complete Integer Recourse
SIAM Journal on Optimization, 1996Summary: The stability of stochastic programs with mixed-integer recourse and random right-hand sides under perturbations of the integrating probability measure is considered from a quantitative viewpoint. Objective-function values of perturbed stochastic programs are related to each other via a variational distance of probability measures based on a ...
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A provably convergent heuristic for stochastic bicriteria integer programming
Journal of Heuristics, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Stochastic Integer Programming Approach to Air Traffic Scheduling and Operations
Operations Research, 2020Alexandre Jacquillat
exaly
Multistage Stochastic Unit Commitment Using Stochastic Dual Dynamic Integer Programming
IEEE Transactions on Power Systems, 2019Xu Andy Sun
exaly

