Model for cost estimation in a finite-capacity stochastic environment based on shop floor optimization combined with simulation

In recent years several researchers suggested cost estimation models that consider limited capacity. These researchers ignored the stochastic nature of the shop floor. This paper presents a cost estimation model that takes into account the stochastic environment. It is based on marginal analysis – the difference between the total cost without the new order and the total cost with the new order. The proposed model is based on the integration of simulation and optimization. Data generated by the simulation is inserted into the optimization procedure that finds good feasible solutions quickly. A significant advantage of the proposed stochastic cost estimation over an existing deterministic approach is shown. A computational study is performed to test different factors affecting the proposed model.