The first part of this work established the foundations of a radial duality between nonnegative optimization problems, inspired by the work of (Renegar, 2016). Here we utilize our radial duality theory to design and analyze projection-free optimization algorithms that operate by solving a radially dual problem. In particular, we consider radial subgradient, smoothing, and accelerated … Read more
(Renegar, 2016) introduced a novel approach to transforming generic conic optimization problems into unconstrained, uniformly Lipschitz continuous minimization. We introduce radial transformations generalizing these ideas, equipped with an entirely new motivation and development that avoids any reliance on convex cones or functions. Perhaps of greatest practical importance, this facilitates the development of new families of … Read more
Truncated singular value decomposition (SVD), also known as the best low-rank matrix approximation, has been successfully applied to many domains such as biology, healthcare, and others, where high-dimensional datasets are prevalent. To enhance the interpretability of the truncated SVD, sparse SVD (SSVD) is introduced to select a few rows and columns of the original matrix … Read more
A total coloring of a graph G = (V, E) is an assignment of colors to vertices and edges such that neither two adjacent vertices nor two incident edges get the same color, and, for each edge, the end-points and the edge itself receive a different color. Any valid total coloring induces a partition of … Read more
We consider a bilevel attacker-defender problem to find the worst-case attack on the relays that control transmission grid components. The attacker infiltrates some number of relays and renders all of the components connected to them inoperable, with the goal of maximizing load shed. The defender responds by minimizing the resulting load shed, re-dispatching using a … Read more
Direct Multisearch (DMS) is a Derivative-free Optimization class of algorithms suited for computing approximations to the complete Pareto front of a given Multiobjective Optimization problem. It has a well-supported convergence analysis and simple implementations present a good numerical performance, both in academic test sets and in real applications. Recently, this numerical performance was improved with … Read more
In this article we address the problem of minimizing a strictly convex quadratic function using a novel iterative method. The new algorithm is based on the well–known Nesterov’s accelerated gradient method. At each iteration of our scheme, the new point is computed by performing a line–search scheme using a search direction given by a linear … Read more
The Simple Plant Location Problem (SPLP) is a well-known NP-hard optimisation problem with applications in logistics. Although many families of facet-defining inequalities are known for the associated polyhedron, very little work has been done on separation algorithms. We present the first ever polynomial-time separation algorithm for the SPLP that separates exactly over an exponentially large … Read more
The Vehicle Allocation Problem (VAP) consists of repositioning empty vehicles across a set of terminals over a given planning horizon so as to maximize the profits generated from serving demand for transportation of goods between pair of terminals. This problem has been classically modeled using an extended space-time network which captures the staging of the … Read more
We consider degree-d forms on the Euclidean unit sphere. We specialize to our setting a genericity result by Nie obtained in a more general framework. We exhibit an homogeneous polynomial Res in the coefficients of f, such that if Res(f) is not zero then all points that satisfy first- and second-order necessary optimality conditions are … Read more