Campus Units
Industrial and Manufacturing Systems Engineering
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
2015
Journal or Book Title
Risk Analysis
Volume
36
Issue
4
First Page
847
Last Page
862
Research Focus Area(s)
Operations Research
DOI
10.1111/risa.12479
Abstract
This article constructs a framework to help a decisionmaker allocate resources to increase his or her organization's resilience to a system disruption, where resilience is measured as a function of the average loss per unit time and the time needed to recover full functionality. Enhancing resilience prior to a disruption involves allocating resources from a fixed budget to reduce the value of one or both of these characteristics. We first look at characterizing the optimal resource allocations associated with several standard allocation functions. Because the resources are being allocated before the disruption, however, the initial loss and recovery time may not be known with certainty. We thus also apply the optimal resource allocation model for resilience to three models of uncertain disruptions: (1) independent probabilities, (2) dependent probabilities, and (3) unknown probabilities. The optimization model is applied to an example of increasing the resilience of an electric power network following Superstorm Sandy.
Copyright Owner
John Wiley & Sons, Inc.
Copyright Date
2016
Language
en
File Format
application/pdf
Recommended Citation
MacKenzie, Cameron A. and Zobel, Christopher W., "Allocating Resources to Enhance Resilience, with Application to Superstorm Sandy and an Electric Utility" (2015). Industrial and Manufacturing Systems Engineering Publications. 69.
https://lib.dr.iastate.edu/imse_pubs/69
Comments
This is the peer reviewed version of the following article: “Allocating Resources to Enhance Resilience, with Application to Superstorm Sandy and an Electric Utility”. Risk Analysis. doi: 10.1111/risa.12479. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for self-archiving.