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Article
Residuals-based distributionally robust optimization with covariate information
We consider data-driven approaches that integrate a machine learning prediction model within distributionally robust optimization (DRO) given limited joint observations of uncertain parameters and covariates. ...
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Article
Special Issue: Global Solution of Integer, Stochastic and Nonconvex Optimization Problems
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Article
Two-stage linear decision rules for multi-stage stochastic programming
Multi-stage stochastic linear programs (MSLPs) are notoriously hard to solve in general. Linear decision rules (LDRs) yield an approximation of an MSLP by restricting the decisions at each stage to be an affin...
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Article
A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs
We propose a stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs. Our approach is based on a bi-objective viewpoint of chance-constrained programs ...
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Article
Branch-and-cut approaches for chance-constrained formulations of reliable network design problems
We study solution approaches for the design of reliably connected networks. Specifically, given a network with arcs that may fail at random, the goal is to select a minimum cost subset of arcs such the probabi...
