PROPORTIONAL LOTSIZING AND SCHEDULING

Two multi-item capacitated dynamic lotsizing and scheduling models wit h a finite horizon have been established recently: the discrete lotsiz ing and scheduling problem as well as the continuous setup lotsizing p roblem. An analysis of the underlying fundamental assumptions provides the basis for introducing a new model, the proportional lotsizing and scheduling problem. We present a new backward-oriented regret-based b iased random sampling method which solves the new model efficiently. T he model is well suited for the incorporation of some of the extension s relevant for practice: setup times, sequence-dependent setup costs ( times), multiple machines as well as multiple stages.