Arc flow-based formulations for extensions of the one-dimensional cutting stock problem

Abstract

The Cutting Stock Problem (CSP) consists in determining the best way to cut bigger objects into small items, and it has been studied for decades. CSP is found in many industrialprocesses, and part of its actual research has focused on extensions and integrations of this problem with other operational aspects found in real industrial systems, for instance, lot sizing and alternative manufacturing modes. The aim of this research project is to study arcflow models for extensions of the one-dimensional CSP. We intend to investigate extensions inspired by industrial applications and which its actual resolution methods lack improvements. To improve its computational performance, we intend to reformulate these problems usingarc flow-based formulations. These formulations have been studied over the years and are powerful tools that allow modeling various combinatorial problems and have presented good results. We intend to develop solutions methods and run performance studies to evaluate computational time, solutions quality and parameters effects on these different problems. (AU)