Simulation of order-up-to levels in a complex logistics with uncertain customer demands

Complex Logistics (CL) is a netlike logistics chain consisting of manufacturer entities, wholesaler entities and retailer entities. This paper describes a simulation tool, CLSim, developed for analyzing CL behavior and performance with uncertain customer demands which are described by imprecise natural language expressions and they are modeled in CLSim by fuzzy sets. Two types of models are combined in CLSim: (1) CL fuzzy analytical models to determine the optimal order-up-to levels for all entities in a CL and (2) a CL simulation model to evaluate CL performance achieved over time by applying the order-up-to levels recommended by the fuzzy models. The application of CLSim in analyzing and quantifying the effects of changing uncertainty in customer demands is discussed and illustrated by a numerical example.