Assessing the reliability and the expected performance of a network under disaster risk.
In a disaster situation, functionality of an infrastructure network is critical for effective emergency response. We evaluate several probabilistic measures of connectivity and expected travel time/distance between critical origin-destination pairs to assess the functionality of a given transportation network in case of a disaster. The input data include the most likely disaster scenarios as well as the probability that each link of the network fails under each scenario. Unlike most studies that assume independent link failures, we model dependency among link failures and propose a novel dependency model that incorporates the impact of the disaster on the network and at the same time yields tractable cases for the computation of the probabilistic measures. We develop algorithms for the computation of the measures and utilize a Monte Carlo simulation algorithm for the intractable cases. We present a case study of the Istanbul highway system under earthquake , and compare different dependency structures computationally. [ABSTRACT FROM AUTHOR]/nCopyright of OR Spectrum is the property of Springer Science & Business Media B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Evaluate several probabilistic measures of connectivity and expected travel time/distance between critical origin–destination pairs to assess the functionality of a given transportation network in case of a disasasterDependency model
Develop algorithms for the computation of the measures and utilize a Monte Carlo simulation algorithm for the intractable cases
Monte Carlo sampling algorithm to estimate the measures under interest for the computationally difficult case of independent link failures for purposes of comparison.
Input data include themost likely disaster scenarios as well as the probability that eachlink of the network fails under each scenario
Our goal in this study was to measure the reliability and the expected post-disasterperformance of a network under disaster
Reliability and performance of a network of realistic size can be estimated with high accuracy in moderate computation time with the proposed Monte Carlo simulation method
Analyze the expected performance of response operations and to see how the urban highway network of Istanbul would perform during an anticipated major earthquake in the region
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