Suggested Citation:
Liu, Changzheng (2009) A Stochastic Programming Approach for Transportation Network Protection. Institute of Transportation Studies, University of California, Davis, Research Report UCD-ITS-RR-09-62

Finding effective strategies of allocating limited mitigation resources to critical infrastructure system components for protection, response, and recovery is among the central tasks of disaster mitigation and management. This dissertation tackles the pre-disaster network protection problem, a specific instance of the above general resource allocation problem, of determining which network components should be protected (e.g. retrofitted or strengthened) before disasters given resource constraints. The most prominent feature of this problem is decision making under uncertainty since disasters are not realized yet and hence uncertain at the time of making protection decisions. A popular method for dealing with uncertainty in the practice of disaster mitigation is scenario analysis. System cost is evaluated under each disaster scenario and scenario dependent policies may be generated. One then can aggregate these scenario dependent policies into an implementable policy or simply take the policy from the most likely scenario. This scenario analysis approach has little possibility to ensure an optimal policy in the sense of optimizing mathematically well defined system measures (e.g. expected loss from disasters).