O'Hanley, J.R., Scaparra, M.P., García-Quiles, S. (2013) Probability chains: A general linearization technique for modeling reliability in facility location and related problems. European Journal of Operational Research, 230 (1). pp. 63-75. ISSN 0377-2217. (doi:10.1016/j.ejor.2013.03.021) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:34015)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1016/j.ejor.2013.03.021 |
Abstract
In this paper, we propose an efficient technique for linearizing facility location problems with site-dependent failure probabilities, focusing on the unreliable p-median problem. Our approach is based on the use of a specialized flow network, which we refer to as a probability chain, to evaluate compound probability terms. The resulting linear model is compact in size. The method can be employed in a straightforward way to linearize similarly structured problems, such as the maximum expected covering problem. We further discuss how probability chains can be extended to problems with co-location and other, more general problem classes. Additional lower bounds as well as valid inequalities for use within a branch and cut algorithm are introduced to significantly speed up overall solution time. Computational results are presented for several test problems showing the efficiency of our linear model in comparison to existing
problem formulations.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.ejor.2013.03.021 |
Uncontrolled keywords: | Facility location; Reliability; Linearization; Probability chains; Probability flow networks; Valid inequalities |
Subjects: | H Social Sciences > HA Statistics > HA33 Management Science |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Jesse O'Hanley |
Date Deposited: | 30 May 2013 10:25 UTC |
Last Modified: | 19 Sep 2023 15:04 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/34015 (The current URI for this page, for reference purposes) |
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