New publication in the Journal of Infrastructure Systems

In this article, the authors give an example of how to optimize restoration schedules for various damage scenarios that would occur following natural hazards, considering

1. different types of damage to roads or bridges and by collecting data on tasks, costs, and times required to restore different damages, and
2. the trade-offs between rapid restoration and a more prolonged, cost-conscious approach.
   

These trade-offs include the facts that

1. quick restoration reduces community disruptions but comes at a higher cost due to expedited resource acquisition, increased labor, and equipment mobilization and conversely, 
2. a slower, budget-conscious approach, while saving on immediate costs, might amplify indirect socioeconomic losses due to prolonged disruptions such as driver delays, reduced accessibility to critical facilities, supply chain interruptions, or impacts on vulnerable populations.  

The optimization proposed uses simulations to generate multiple schedule solutions for each scenario using probabilistic distributions of tasks and their precedence relations to find the optimal schedule. Data on damages and associated costs and times are based on 15 years of data from Iowa, United States, which were reported as part of the detailed damage inspection reports submitted to receive emergency relief funds by Iowa Department of Transportation. It covers 10 bridge and six road damage scenarios.The work is part of a collaboration with external page Prof. Alice Alipour from Iowa State University.

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