Optimization Online

We present a model and an exact solution method for single-source capacitated facility location problems with decision-dependent demand uncertainty. The model allows the joint probability distribution of customer demands to depend on the facility to which demand points are allocated. The number of possible decision-dependent distributions is therefore equal to the number of feas...

We quantify the robust value lost by restricting Wasserstein transport to a common low-dimensional subspace. Affine transport sets and outer moment sets yield exact bounds for quadratic losses with nonsingular nominal covariance. A spectral rule augments a prescribed base space and attains a sharp, base-dependent approximation factor for the aggregate first-order restriction los...

Winner determination in combinatorial auctions is a weighted set-packing problem and is NP-hard in general. This paper develops a deterministic polynomial-time sparse-pursuit framework that couples the global linear-programming relaxation with CoSaMP-type identify–merge–re-estimate–prune dynamics. The re-estimation step keeps only a logarithmic-size moving window integral while ...

Random Reshuffling (RR) is the default data-ordering strategy in practice, and it is almost always run with minibatches. The recent theory of Liu shows that single-sample RR dominates SGD in smooth convex optimization for every stepsize below \(2/\hat{L}\), but the role of the batch size has not been worked out. In this note we study ...

Quantum optimization has emerged at the intersection of quantum computing and operations research, driven by the prospect of addressing challenging combinatorial optimization problems through quantum and quantum-inspired computational approaches. This paper provides a structured review of the field from a past, present, and future perspective. We first trace the evolution of qua...