Гарантирующие и оптимистические решения задач целочисленной оптимизации с выпуклыми квадратичными функциями ограничений

Abstract

The paper studies complex integer optimization problems with inexact coefficients of linear objective function and convex quadratic function of constraints. Exact and approximate decomposition methods are developed and proved for search of guaranteeing and optimistic solutions to such problems. The paper proposes some classes of uncertainty sets that describe input data of such problems.