Abstract
This work proposes a framework for the optimization of postdisaster road network restoration strategies from a perspective of resilience. The network performance is evaluated by the total system travel time (TSTT). After the implementation of a postdisaster restoration schedule, the network flows in a certain period of days are on a disequilibrium state; thus, a link-based day-to-day traffic assignment model is employed to compute TSTT and simulate the traffic evolution. Two indicators are developed to assess the road network resilience, i.e., the resilience of performance loss and the resilience of recovery rapidity. The former is calculated based on TSTT, and the latter is computed according to the restoration makespan. Then, we formulate the restoration optimization problem as a resilience-based bi-objective mixed integer programming model aiming to maximize the network resilience. Due to the NP-hardness of the model, a genetic algorithm is developed to solve the model. Finally, a case study is conducted to demonstrate the effectiveness of the proposed method. The effects of key parameters including the number of work crews, travelers’ sensitivity to travel time, availability of budget, and decision makers’ preference on the values of the two objectives are investigated as well.
Highlights
Road infrastructure forms the backbone of transport activities, which plays an important role in boosting economic development and increasing accessibility
Ere is an increasing demand for making a cost-effective postdisaster road network restoration strategy (RNRS) [1, 2], which refers to determining the road segments to be repaired and the restoration time sequence
This study aims to investigate the optimal postdisaster restoration problem for road networks from the perspective of resilience considering the day-to-day network flow fluctuation. e main contribution of our work is to build a resilience-based bi-objective mixed integer programming model combined with a link-based day-to-day traffic assignment model to determine the optimal RNRS based on the tradeoff between the maximal resilience of performance loss and the maximal resilience of recovery rapidity
Summary
Road infrastructure forms the backbone of transport activities, which plays an important role in boosting economic development and increasing accessibility. Ere is an increasing demand for making a cost-effective postdisaster road network restoration strategy (RNRS) [1, 2], which refers to determining the road segments to be repaired and the restoration time sequence. A variety of metrics have been introduced to assess the resilience of an infrastructure network. This study aims to investigate the optimal postdisaster restoration problem for road networks from the perspective of resilience considering the day-to-day network flow fluctuation. Decision makers would determine a set of prioritized road segments to be restored and the optimal time sequence of the restoration tasks.
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