The effects of pre or post delay variable changes in discrete event simulation and combined DES/system dynamics approaches in modelling supply chain performance

Discrete Event Simulation (DES) is the main tool used in analyzing supply chains (SCs). In many simulation studies the effect of the modeling approach on SC performance is ignored. Many researches have overlooked the fact that in DES where events are the drivers of variable changes; the modeler has the option to change these variables pre or post delay event occurrence. In SCs this choice is critical and has a significant effect on the results obtained. Another modeling approach is System Dynamics (SD) which overcomes the difficulties of DES because variables do not change in discrete jumps but rather smoothly overtime. Both DES and SD approaches are combined in one model and are compared to two types of DES modeling approaches; Pre-delay and Post-delay DES. A case study is implemented in a local cement SC. Inventory levels (IL), holding costs (HC) and ordering costs (OC) for the Combined DES/SD model are shown to be between those of the other two models. Post-delay DES is shown to overestimate IL and HC but underestimate OC; while, Pre- delay DES is shown to underestimate IL and HC while overestimating OC.