2021/11/11 by Javier Zazo, Zazo, Javier, Santiago Zazo +1
Computer Science · Mathematics · #Optimization and Variational Analysis #Advanced Optimization Algorithms Research #Optimization and Search Problems
paper · pdf · doi:10.48550/arxiv.2111.06490
We study nonconvex quadratic problems (QPs) with quadratic separable\nconstraints, where these constraints can be defined both as inequalities or\nequalities. We derive sufficient conditions for these types of problems to\npresent the S-property, which ultimately guarantees strong duality between the\nprimal and dual problems of the QP. We study the existence of solutions and\npropose a novel distributed algorithm to solve the problem optimally when the\nS-property is satisfied. Finally, we illustrate our theoretical results proving\nthat the robust least squares problem with multiple constraints has the strong\nduality property.\n