Reproduce “Robust Out-of-Distribution Stochastic Optimization” on OpenResearch
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About this paper
Xianyu Li, Huan Xu, Xiaolin Huang, Chao Shang
RooD-SO helps retailers order new products without sales histories by learning demand patterns from related products. It treats source and target distributions as draws from a shared unknown meta-distribution and chooses an order against the learned set’s worst case. In a newsvendor test, average cost was −20.66 versus −18.04 for DRO-Conv; its guarantees apply asymptotically to draws from that meta-distribution.
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