Joint location-two-echelon-inventory supply chain model with stochastic demand

Malek Abu Alhaj, Ali Diabat

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Existing supply chain location-inventory models optimize over inventory policies and distribution center locations, but use a deterministic approach that does not take into consideration the uncertainty of demand. We present an extension to the deterministic multi-echelon joint location-inventory model that adds uncertainty by including a new variable that reflects the probability of different scenarios. We test the model using three different demand scenarios. To compare the results for the stochastic case with those of the deterministic case, the model is solved as a deterministic model under one scenario, and the cost of assuming a scenario other than the true scenario is calculated.

Original languageEnglish (US)
Title of host publication41st International Conference on Computers and Industrial Engineering 2011
PublisherComputers and Industrial Engineering
Pages25-30
Number of pages6
ISBN (Print)9781627486835
StatePublished - 2011
Event41st International Conference on Computers and Industrial Engineering 2011 - Los Angeles, CA, United States
Duration: Oct 23 2011Oct 25 2011

Publication series

Name41st International Conference on Computers and Industrial Engineering 2011
Volume2011-January

Other

Other41st International Conference on Computers and Industrial Engineering 2011
CountryUnited States
CityLos Angeles, CA
Period10/23/1110/25/11

Keywords

  • Integer programming
  • Location problem
  • Supply chains
  • Uncertainty modeling

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Industrial and Manufacturing Engineering

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  • Cite this

    Alhaj, M. A., & Diabat, A. (2011). Joint location-two-echelon-inventory supply chain model with stochastic demand. In 41st International Conference on Computers and Industrial Engineering 2011 (pp. 25-30). (41st International Conference on Computers and Industrial Engineering 2011; Vol. 2011-January). Computers and Industrial Engineering.