Convex optimization problems in supply chain planning and their solution by a column generation method based on the Frank Wolfe method

Abstract

Many problems in supply chain optimization concern the minimization of a differentiable convex objective function subject to a set of linear constraints. The aim of this work is to present a number of such problems and to propose an efficient method for their solution. The proposed method is based on improvements of the well known Frank-Wolfe algorithm. The computational results of the proposed algorithm demonstrate its effectiveness and efficiency.