Robust strategies for facility location under uncertainty
This paper considers a stochastic facility location problem in which multiple capacitated facilities serve customers with a single product, and a stockout probabilistic requirement is stated as a chance constraint. Customer demand is assumed to be uncertain and to follow either a normal or an ambiguous distribution. We study robust approximations to the problem in order to incorporate information about the random demand distribution in the best possible, computationally tractable way. We also discuss how a decision maker’s risk preferences can be incorporated in the problem through robust optimization. Finally, we present numerical experiments that illustrate the performance of the different robust formulations. Robust optimization strategies for facility location appear to have better worst-case performance than nonrobust strategies. They also outperform nonrobust strategies in terms of realized average total cost when the actual demand distributions have higher expected values than the expected values used as input to the optimization models.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gulpinar, Nalan & Rustem, Berc, 2007. "Robust optimal decisions with imprecise forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3595-3611, April.
- Aharon, Ben-Tal & Boaz, Golany & Shimrit, Shtern, 2009. "Robust multi-echelon multi-period inventory control," European Journal of Operational Research, Elsevier, vol. 199(3), pages 922-935, December.
- Yao, Zhishuang & Lee, Loo Hay & Jaruphongsa, Wikrom & Tan, Vicky & Hui, Chen Fei, 2010. "Multi-source facility location-allocation and inventory problem," European Journal of Operational Research, Elsevier, vol. 207(2), pages 750-762, December.
- E S Sheppard, 1974. "A conceptual framework for dynamic location - allocation analysis," Environment and Planning A, Pion Ltd, London, vol. 6(5), pages 547-564, May.
- Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
- Owen, Susan Hesse & Daskin, Mark S., 1998. "Strategic facility location: A review," European Journal of Operational Research, Elsevier, vol. 111(3), pages 423-447, December.
- Berman, Oded & Krass, Dmitry & Tajbakhsh, M. Mahdi, 2012. "A coordinated location-inventory model," European Journal of Operational Research, Elsevier, vol. 217(3), pages 500-508.
- Karthik Natarajan & Dessislava Pachamanova & Melvyn Sim, 2008. "Incorporating Asymmetric Distributional Information in Robust Value-at-Risk Optimization," Management Science, INFORMS, vol. 54(3), pages 573-585, March.
- Zuo-Jun Max Shen & Mark S. Daskin, 2005. "Trade-offs Between Customer Service and Cost in Integrated Supply Chain Design," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 188-207, September.
When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:225:y:2013:i:1:p:21-35. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If references are entirely missing, you can add them using this form.