Modelling, simulation, and analysis of supply chain systems using discrete-event simulation.

摘要

Many approaches have been developed which support the construction of detailedudsupply chain models useful for analysis and simulation. However, most of theseudapproaches lack the ability to model the supply chain in a single model, and usuallyudproduce solutions that lead to conflicting strategies between the companies.udSimulation using a discrete-event simulation (DES) is an effective tool for theuddynamically changing supply chain variables, thus allowing the system to beudmodelled more realistically. Considering the complexities of the supply chain systemudand the interrelations between its various systems, the task of developing such audmodel is challenging. The aim of this thesis is to develop a simulation model of a fastudmoving consumer goods (FMCG) supply chain with a DES tool. This model would beudutilised as a decision-support system (DSS) for the investigation of the effectivenessudof several inventory policies towards effective coordination and control of production inventoryudsystem, in various situations.udThis thesis discusses fundamental issues in the development of a simulation modeludfor a supply chain using the DES tool, ARENA. A modelling procedure for theuddevelopment of a supply chain simulation model is presented. The overall structure ofudthe model is constructed by incorporating the well documented concept of modellingudmaterials flowing downstream with an approach of modelling orders flowing upstreamud(modelling of feedback information). The model has an easily adaptable structureudwhere rules (inventory policies) and model variables can be modified. The flexibility inudthe model's structure allows devising appropriate experimental designs, for severaludtests to be performed to imitate some realistic situations or scenarios (including theudpresence of disturbances). A new control theory oriented inventory policy, called theudpseudo PID, is proposed. Detailed evaluations of five inventory policies for audproduction-inventory control under dynamic and stochastic conditions is presented.udThe findings demonstrate the ability of the approach to provide a wealth of potentialudsolutions to the decision-maker, and confirm the qualitative behaviour of a supplyudchain in response to the different policies.