A Stochastic Optimization Model to Reduce Expected Post-Disaster Response Time Through Pre-Disaster Investment Decisions

Lili Du () and Srinivas Peeta ()

Networks and Spatial Economics, 2014, vol. 14, issue 2, 295 pages

Abstract: This paper seeks to enhance network survivability under a disaster and reduce the expected post-disaster response time for transportation networks through pre-disaster investment decisions. The planning focuses on determining the links of the network to strengthen through investment under two types of uncertainties: the disaster characteristics, and the surviving network under each disaster. A bi-level stochastic optimization model is proposed for this problem, in which link investment decisions are made at the upper level to enhance the network survivability subject to a budget constraint such that the expected post-disaster response time is minimized at the lower level. A two-stage heuristic algorithm is proposed to obtain effective solutions efficiently. The numerical experiments indicate that the proposed heuristic algorithm converges to a fixed point representing a feasible solution, within an acceptable tolerance level, of the bi-level stochastic optimization model which is an effective solution under disasters of moderate severity. Parametric and sensitivity analyses reinforce the need for a holistic approach that integrates multiple relevant considerations to determine the link investment decisions. Copyright Springer Science+Business Media New York 2014

Keywords: Pre-disaster investment decisions; Network survivability; Post-disaster response times; Bi-level stochastic optimization (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (18)

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DOI: 10.1007/s11067-013-9219-1

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