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
PDF (Portable Document Format)
294 KB
Created on 7/11/2014
Views: 1635
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