A primal cutting-set algorithm with convergence guarantees solves standard, almost-sure, chance-constrained, and locally informed distributionally robust optimization over closed, potentially unbounded sample spaces.
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A Primal Perspective on Distributionally Robust Optimization: An Investigation on Modeling and Solution Strategies
A primal cutting-set algorithm with convergence guarantees solves standard, almost-sure, chance-constrained, and locally informed distributionally robust optimization over closed, potentially unbounded sample spaces.