Title: Supply chain risk management via correlated scenario analysis

Authors: Erhan Deniz, James T. Luxhoj

Addresses: Department of Industrial and Systems Engineering, Rutgers University, Piscataway, New Jersey 08854, USA. ' Department of Industrial and Systems Engineering, Rutgers University, Piscataway, New Jersey 08854, USA

Abstract: In this paper, we study a comprehensive Supply Chain (SC) optimisation model that incorporates the uncertainty associated with demand, market price, supply and procurement costs. A number of correlated scenarios are built each of which represents a set of possible realisations of those random factors. Taking a stochastic programming approach, the variables and parameters are transformed into a Mixed Integer Programming (MIP) model, where the objective is to maximise the net present value of the cash flow for the whole SC over a finite planning horizon. The proposed model provides a useful tool for both strategic (e.g. locations and capacities of facilities) and operational (e.g. material flow) SC decision making.

Keywords: SCRM; supply chain risk management; stochastic programming; MIP; mixed integer programming; scenario analysis; supply chain management; SCM; supply chain optimisation; uncertainty; modelling.

DOI: 10.1504/IJISM.2008.020756

International Journal of Integrated Supply Management, 2008 Vol.4 No.3/4, pp.278 - 302

Published online: 14 Oct 2008 *

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