Finite capacity planning is a central problem in manufacturing industries. At the heart of it lies a scheduling optimization problem, which has been so far studied in the optimization literature mainly in abstract forms, like job shop scheduling. There is a huge gap between the job shop instances used as benchmark in the literature and the scheduling instances met in real-world planning, this both with respect to instance size and to instance complexity, meaning the type of constraints and of variables considered. We present here the algorithmic core of a package primarily targeted to metallic carpentry industries, where instance types and CPU time constraints pose severe burdens on the optimization methods which can be used. We report about the results obtained by means of partial enumeration, a mathematic programming technique, here included in an Ant Colony Optimization framework.
Real World Finite Capacity Planning: A Partial Enumeration – Based Optimizer / Bianco E.; Boschetti M.; Maniezzo V.; Mingozzi A.. - ELETTRONICO. - (2009). (Intervento presentato al convegno 13th IFAC Symposium on Information Control Problems in Manufacturing tenutosi a V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences, Moscow, Russia nel June 3 - 5, 2009).
Real World Finite Capacity Planning: A Partial Enumeration – Based Optimizer
BOSCHETTI, MARCO ANTONIO;MANIEZZO, VITTORIO;MINGOZZI, ARISTIDE
2009
Abstract
Finite capacity planning is a central problem in manufacturing industries. At the heart of it lies a scheduling optimization problem, which has been so far studied in the optimization literature mainly in abstract forms, like job shop scheduling. There is a huge gap between the job shop instances used as benchmark in the literature and the scheduling instances met in real-world planning, this both with respect to instance size and to instance complexity, meaning the type of constraints and of variables considered. We present here the algorithmic core of a package primarily targeted to metallic carpentry industries, where instance types and CPU time constraints pose severe burdens on the optimization methods which can be used. We report about the results obtained by means of partial enumeration, a mathematic programming technique, here included in an Ant Colony Optimization framework.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
