Supply chain risk management via correlated scenario analysis

Erhan Deniz, James Luxhoj

Research output: Contribution to journalArticle

3 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)278-302
Number of pages25
JournalInternational Journal of Integrated Supply Management
Volume4
Issue number3-4
DOIs
StatePublished - Oct 28 2008

All Science Journal Classification (ASJC) codes

  • Marketing
  • Strategy and Management

Keywords

  • MIP
  • Mixed integer programming
  • SCRM
  • Scenario analysis
  • Stochastic programming
  • Supply chain risk management

Fingerprint Dive into the research topics of 'Supply chain risk management via correlated scenario analysis'. Together they form a unique fingerprint.

  • Cite this