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Analysis of facility protection strategies against an uncertain number of attacks: The Stochastic R-Interdiction Median Problem with Fortification.

Liberatore, Federico, Scaparra, Maria Paola, Daskin, Mark S. (2011) Analysis of facility protection strategies against an uncertain number of attacks: The Stochastic R-Interdiction Median Problem with Fortification. Computers and Operations Research, 38 (1). pp. 357-366. ISSN 0305-0548. (doi:10.1016/j.cor.2010.06.002) (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)

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. (Contact us about this Publication)
Official URL
https://doi.org/10.1016/j.cor.2010.06.002

Abstract

We present the Stochastic R-Interdiction Median Problem with Fortification (S-RIMF). This model optimally allocates defensive resources among facilities to minimize the worst-case impact of an intentional disruption. Since the extent of terrorist attacks and malicious actions is uncertain, the problem deals with a random number of possible losses. A max-covering type formulation for the S-RIMF is developed. Since the problem size grows very rapidly with the problem inputs, we propose pre-processing techniques based on the computation of valid lower and upper bounds to expedite the solution of instances of realistic size. We also present heuristic approaches based on heuristic concentration-type rules. The heuristics are able to find an optimal solution for almost all the problem instances considered. Extensive computational testing shows that both the optimal algorithm and the heuristics are very successful at solving the problem. Finally, a discussion of the importance of recognizing the stochastic nature of the number of possible attacks is provided.

Item Type: Article
DOI/Identification number: 10.1016/j.cor.2010.06.002
Subjects: H Social Sciences
Divisions: Faculties > Social Sciences > Kent Business School > Business process/operations
Faculties > Social Sciences > Kent Business School > Centre for Logistics and Heuristic Organisation (CLHO)
Depositing User: K. Senyszyn
Date Deposited: 03 Mar 2011 12:47 UTC
Last Modified: 29 May 2019 08:27 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/27454 (The current URI for this page, for reference purposes)
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