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

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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.

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Authors and Affiliations

  1. Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, IL, 60616, USA

    Lili Du

  2. School of Civil Engineering, Purdue University, West Lafayette, IN, 47907, USA

    Srinivas Peeta

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  1. Lili Du
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  2. Srinivas Peeta
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Correspondence to Srinivas Peeta.

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Du, L., Peeta, S. A Stochastic Optimization Model to Reduce Expected Post-Disaster Response Time Through Pre-Disaster Investment Decisions. Netw Spat Econ 14, 271–295 (2014). https://doi.org/10.1007/s11067-013-9219-1

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