Risk Management in Uncapacitated Facility Location Models with Random Demands
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Joyendu Bhadury, Professor, Information Systems and Supply Chain Management (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
Abstract: In this paper we consider a location-optimization problem where the classical uncapacitated facility location model is recast in a stochastic environment with several risk factors that make demand at each customer site probabilistic and correlated with demands at the other customer sites. Our primary contribution is to introduce a new solution methodology that adopts the mean–variance approach, borrowed from the finance literature, to optimize the “Value-at-Risk” (VaR) measure in a location problem. Specifically, the objective of locating the facilities is to maximize the lower limit of future earnings based on a stated confidence level. We derive a nonlinear integer program whose solution gives the optimal locations for the p facilities under the new objective. We design a branch-and-bound algorithm that utilizes a second-order cone program (SOCP) solver as a subroutine. We also provide computational results that show excellent solution times on small to medium sized problems.
Risk Management in Uncapacitated Facility Location Models with Random Demands
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Created on 7/11/2014
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Additional Information
- Publication
- Computers & Operations Research, 36(4), 1002-1011
- Language: English
- Date: 2009
- Keywords
- Facility location, Risk management, Second-order cone programming, Value-at-Risk