Optimal Design of Large-Scale Supply Chain with Multi-Echelon Inventory and Risk Pooling under Demand Uncertainty

Fengqi You*, Ignacio E. Grossmann

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

10 Scopus citations

Abstract

We address the optimal design of a multi-echelon supply chain and the associated inventory systems in the presence of uncertain customer demands. By using the guaranteed service approach to model the multi-echelon stochastic inventory system, we develop an optimization model for simultaneously optimizing the transportation, inventory and network structure of a multi-echelon supply chain. We formulate this problem as an MINLP with a nonconvex objective function including bilinear, trilinear and square root terms. By exploiting the properties of the basic model, we reformulate the problem as a separable concave minimization program. A spatial decomposition algorithm based on Lagrangean relaxation and piecewise linear approximation is proposed to obtain near global optimal solutions with reasonable computational expense. Examples for industrial gas supply chains with up to 5 plants, 50 potential distribution centers and 100 markets are presented.

Original languageEnglish (US)
Title of host publication19th European Symposium on Computer Aided Process Engineering
EditorsJacek Jezowski, Jan Thullie
Pages991-996
Number of pages6
DOIs
StatePublished - Jun 26 2009

Publication series

NameComputer Aided Chemical Engineering
Volume26
ISSN (Print)1570-7946

Keywords

  • MINLP
  • Risk-pooling
  • Safety Stock
  • Supply Chain
  • Uncertainty

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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