Convex Ternary Quartics Are SOS-Convex
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Global Optimization
A Bilevel Hierarchy of Strengthened Complex Moment Relaxations for Complex Polynomial Optimization
This paper proposes a bilevel hierarchy of strengthened complex moment relaxations for complex polynomial optimization. The key trick entails considering a class of positive semidefinite conditions that arise naturally in characterizing the normality of the so-called shift operators. The relaxation problem in this new hierarchy is parameterized by the usual relaxation order as well as … Read more
Revisiting the fitting of the Nelson-Siegel and Svensson models
The Nelson-Siegel and the Svensson models are two of the most widely used models for the term structure of interest rates. Even though the models are quite simple and intuitive, fitting them to market data is numerically challenging and various difficulties have been reported. In this paper, a novel mathematical analysis of the fitting problem … Read more
The best approximation pair problem relative to two subsets in a normed space
In the classical best approximation pair (BAP) problem, one is given two nonempty, closed, convex and disjoint subsets in a finite- or an infinite-dimensional Hilbert space, and the goal is to find a pair of points, each from each subset, which realizes the distance between the subsets. We discuss the problem in more general normed … Read more
ε-Optimality in Reverse Optimization
The purpose of this paper is to completely characterize the global approximate optimality (ε-optimality) in reverse convex optimization under the general nonconvex constraint “h(x) ≥ 0″. The main condition presented is obtained in terms of Fenchel’s ε-subdifferentials thanks to El Maghri’s ε-efficiency in difference vector optimization [J. Glob. Optim. 61 (2015) 803–812], after converting the … Read more
Lipschitz Based Lower Bound Construction for Surrogate Optimization
Bounds play a vital role in guiding optimization algorithms by enhancing convergence, improving solution quality, and quantifying optimality gaps. While Lipschitz-based lower bounds are well-established, their effectiveness is often constrained by the function’s topological properties. To address these limitations, we propose an approach that integrates nonlinear distance metrics with surrogate approximations, yielding more adaptive and … Read more
Refined TSSOS
The moment-sum of squares hierarchy by Lasserre has become an established technique for solving polynomial optimization problems. It provides a monotonically increasing series of tight bounds, but has well-known scalability limitations. For structured optimization problems, the term-sparsity SOS (TSSOS) approach scales much better due to block-diagonal matrices, obtained by completing the connected components of adjacency … Read more
Sparse Polynomial Optimization with Unbounded Sets
This paper considers sparse polynomial optimization with unbounded sets. When the problem possesses correlative sparsity, we propose a sparse homogenized Moment-SOS hierarchy with perturbations to solve it. The new hierarchy introduces one extra auxiliary variable for each variable clique according to the correlative sparsity pattern. Under the running intersection property, we prove that this hierarchy … Read more
Solving moment and polynomial optimization problems on Sobolev spaces
Using standard tools of harmonic analysis, we state and solve the problem of moments for positive measures supported on the unit ball of a Sobolev space of multivariate periodic trigonometric functions. We describe outer and inner semidefinite approximations of the cone of Sobolev moments. They are the basic components of an infinite-dimensional moment-sums of squares … Read more
A Cutting-Plane Global Optimization Algorithm for a Special Non-Convex Problem
This study establishes the convergence of a cutting-plane algorithm tailored for a specific non-convex optimization problem. The presentation begins with the problem definition, accompanied by the necessary hypotheses that substantiate the application of a cutting plane. Following this, we develop an algorithm designed to tackle the problem. Lastly, we provide a demonstration that the sequence … Read more