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Control Theoretic Modeling and Simulation of Supply Chain Management System
Author(s) -
Rehman Obaid Ur,
Ryan Michael J.
Publication year - 2017
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2017.00450.x
Subject(s) - supply chain , toolbox , computer science , stability (learning theory) , monte carlo method , mathematical optimization , work (physics) , supply chain management , engineering , mathematics , mechanical engineering , statistics , machine learning , political science , law , programming language
Control theoretic modelling approaches are very effective in developing a dynamical model of a system. A supply chain system is a dynamical system which contains a number of lead times among supply nodes and is susceptible to demand variation. Control theoretic modelling approaches are proved to be very effective in developing ordering policies for such systems. In this work, we developed a linear discrete time model of a supply chain with multiple supply nodes and pure delays. The model presented here can be used to develop an optimal ordering and distribution policy so that the entire system remains stable. In addition to the mathematical model of the supply chain, a simulation model is also developed using Simulink® toolbox SimEvents®. The simulation model can be used to test various ordering policies to determine system stability. In this work the simulation model is used to test system stability and can be further used to find optimum ordering and optimum routing policies under uncertainty by running a Monte Carlo type simulation using the developed simulation model.