Resilience-based performance modeling and decision optimization for transportation network

TL;DR

This paper introduces a comprehensive resilience-based framework for transportation networks, including a novel performance metric, WIPW, and optimization methods for pre- and post-disaster decision-making to enhance resilience and recovery efficiency.

Contribution

It proposes the WIPW metric for assessing transportation network resilience and develops a decision-making framework for prioritizing retrofit projects and recovery strategies.

Findings

WIPW allows for comparison of resilience improvement options.

The recovery scheduling method reduces total recovery time.

The framework improves post-disaster recovery efficiency.

Abstract

This research presented a novel resilience-based framework to support resilience planning regarding pre-disaster mitigation and post-disaster recovery. First, the author proposes a new performance metric for transportation network, weighted number of independent pathways (WIPW), integrating the network topology, redundancy level, traffic patterns, structural reliability of network components, and functionality of the network during community's post-disaster recovery in a systematical way. To the best of our knowledge, WIPW is the only performance metric that permits risk mitigation alternatives for improving transportation network resilience to be compared on a common basis. Based on the WIPW, a decision methodology of prioritizing transportation network retrofit projects is developed. Second, our studies extend from pre-disaster mitigation to post-hazard recovery, in which this research presents two metrics to evaluate the restoration over the horizon after disasters . That is, total recovery time and the skew of the recovery trajectory. Both metrics are involved in the multi-objective stochastic optimization problem of restoration scheduling. The metrics provided a new dimension to evaluate the relative efficiency of alternative network recovery strategies. The author then develops a restoration scheduling methodology for network post-disaster recovery that minimizes the overall network recovery time and optimizes the recovery trajectory, which ultimately will reduce economic losses due to network service disruption.