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Annals of Operations Research

, Volume 271, Issue 2, pp 551–574 | Cite as

Stochastic multi-site supply chain planning in textile and apparel industry under demand and price uncertainties with risk aversion

  • Houssem FelfelEmail author
  • Wafa Ben Yahia
  • Omar Ayadi
  • Faouzi Masmoudi
Original Research
  • 127 Downloads

Abstract

A multi-product, multi-period, multi-site supply chain production and transportation planning problem, in the textile and apparel industry, under demand and price uncertainties is considered in this paper. The problem is formulated using a two-stage stochastic programming model taking into account the production amount, the inventory and backorder levels as well as the amounts of products to be transported between the different plants and customers in each period. Risk management is addressed by incorporating a risk measure into the stochastic programming model as a second objective function, which leads to a multi-objective optimization model. The objectives aim to simultaneously maximize the expected net profit and minimize the financial risk measured. Two risk measures are compared: the conditional-value-at-risk and the downside risk. As the considered objective functions conflict with each other’s, the problem solution is a front of Pareto optimal robust alternatives, which represents the trade-off among the different objective functions. A case study using real data from textile and apparel industry in Tunisia is presented to illustrate the effectiveness of the proposed model and the robustness of the obtained solutions.

Keywords

Multi-site supply chain Textile and apparel industry Multi-objective optimization Stochastic programming Risk management 

Notes

Acknowledgements

Financial support received from the Mobility of researchers and research for the creation of value (MOBIDOC) is fully appreciated. LINDO Systems, Inc is also acknowledged for giving us a free educational research license of the extended version of LINGO 15.0 software package.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Houssem Felfel
    • 1
    Email author
  • Wafa Ben Yahia
    • 1
  • Omar Ayadi
    • 1
  • Faouzi Masmoudi
    • 1
  1. 1.Mechanics, Modeling and Production LaboratoryUniversity of Sfax, National Engineering School of Sfax (ENIS)SfaxTunisia

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