A Stochastic Lot-Sizing and Scheduling Model

Companies are trying to improve their ability to deliver and to reduce their production costs simultaneously. Nevertheless ongoing orders of customers are causing difficulties to deliver because of bottlenecks in the production. Furthermore constantly incoming customer orders effect that every actual optimal production plan with its already realized and planned guidelines has induced states that are not anymore ideal for further production. In addition, current production planning tools neglect the continuation of the production beyond the planning horizon. Our purpose is to develop a new tool for production planning. As a first step, we propose a production planning model which includes scheduling, lot-sizing, dynamic demand, sequence dependent setup times, backlogging, stockouts, parallel machines, and, last but not least, a careful injection of stochastic data.