Cappanera, Paola, Scaparra, Maria Paola (2011) Optimal allocation of protective resources in shortest path networks. Transportation Science, 45 (1). pp. 64-80. ISSN 0041-1655. (doi:10.1287/trsc.1100.0340) (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:27441)
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/10.1287/trsc.1100.0340 |
Abstract
This article introduces a game theoretic approach for allocating protection resources among the components of a network so as to maximize its robustness to external disruptions. Specifically, we consider shortest-path networks where disruptions may result in traffic flow delays through the affected components or in the complete loss of some elements. A multi-level program is proposed to identify the set of components to harden so as to minimize the length of the shortest path between a supply node and a demand node
after a worst-case disruption of some unprotected components. An implicit enumeration algorithm is then developed to solve the multi-level problem to optimality. The approach is streamlined by solving the lower level interdiction problem heuristically at each node of an enumeration tree and by using some variable fixing rules to reduce the dimension of the lower level problems. A thorough computational investigation demonstrates that the proposed solution method is able to identify optimal protection strategies for networks of significant size. The paper is concluded with a study of the sensitivity of the solution
approach to variations of the problem parameters, such as the level of disruption and protective resources, and the distribution of the arc lengths and delays.
Item Type: | Article |
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DOI/Identification number: | 10.1287/trsc.1100.0340 |
Subjects: |
Q Science H Social Sciences > HD Industries. Land use. Labor > HD29 Operational Research - Applications |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Funders: | Engineering and Physical Sciences Research Council (https://ror.org/0439y7842) |
Depositing User: | Paola Scaparra |
Date Deposited: | 29 Jun 2011 16:33 UTC |
Last Modified: | 19 Sep 2023 15:04 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/27441 (The current URI for this page, for reference purposes) |
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