Split cuts are arguably the most effective class of cutting planes within a branch-and-cut framework for solving general Mixed-Integer Programs (MIP). Sparsity, on the other hand, is a common characteristic of MIP problems, and it is an important part of why the simplex method works so well inside branch-and-cut. In this work, we evaluate the … Read more
We construct web-shaped norming meshes on starlike polygons, by radial and boundary Chebyshev points. Via the approximation theoretic notion of Dubiner distance, we get a (1-eps)-approximation to the minimum of an arbitrary polynomial of degree n by O(n^2/eps) sampling points. Citation Preprint, July 2018 Article Download View Polynomial Optimization on Chebyshev-Dubiner Webs of Starlike Polygons
Consider the multi-objective ranking and selection (MORS) problem in which we select the Pareto-optimal set from a finite set of systems evaluated on three or more stochastic objectives. Solving this problem is difficult because we must determine how to allocate a simulation budget among the systems to minimize the probability that any systems are misclassified. … Read more
Given a point x inside a polytope P and a direction d, the projection of x along d asks to find the maximum step length t such that x+td is feasible; we say x+td is a pierce point because it belongs to the boundary of P. We address this projection sub-problem with arbitrary interior points … Read more
The stochastic Frank-Wolfe method has recently attracted much general interest in the context of optimization for statistical and machine learning due to its ability to work with a more general feasible region. However, there has been a complexity gap in the guaranteed convergence rate for stochastic Frank-Wolfe compared to its deterministic counterpart. In this work, … Read more
This paper considers a multiperiod Emergency Medical Services (EMS) location problem and introduces two two-stage stochastic programming formulations that account for uncertainty about emergency demand. While the first model considers both a constraint on the probability of covering the realized emergency demand and minimizing the expected cost of doing so, the second one employs probabilistic … Read more
This paper investigates a drayage problem generalizing a previously proposed, which is motivated by a case study of a real maritime carrier. To serve export and import customer requests in the hinterland of a port, a fleet of trucks able to carry one or two containers of the same size is adopted. The aim of … Read more
We propose a method, called ACQUIRE, for the solution of constrained optimization problems modeling the restoration of images corrupted by Poisson noise. The objective function is the sum of a generalized Kullback-Leibler divergence term and a TV regularizer, subject to nonnegativity and possibly other constraints, such as flux conservation. ACQUIRE is a line-search method that … Read more
In a recent paper, Lucambio Pérez and Prudente extended the Wolfe conditions for the vector-valued optimization. Here, we propose a line search algorithm for finding a step-size satisfying the strong Wolfe conditions in the vector optimization setting. Well definiteness and finite termination results are provided. We discuss practical aspects related to the algorithm and present … Read more
The Bikesharing allocation and rebalancing problem is the problem of determining the initial daily allocation of bikes to stations in a bikesharing system composed of one depot and multiple capacitated stations, in which bikes can be rebalanced at a point in time later in the day. We propose a two-stage stochastic programming formulation, where the … Read more