# Emergency Repair Scheduling Model for Road Network Integrating Rescheduling Feature
## 2 Literature Review  
Due to the significant impact of natural disasters, there is no single assessment measure alone that can fully describe the road network destruction caused by natural disasters. To generalize possible road damage conditions, they can be categorized in the following three levels [26]:  
1. Total destruction, if the road embankment needs to be reconstructed. 2. Partial damage, if the road section is closed for road surface repairs or minor stabilization of the road embankment. 3. Only sedimentation on the road surface that does not require any repair work. For example, [PERSON] et al. [27] reported the severe damage that occurred in Los Angeles County, California, which was caused by a winter storm in 2005, hit by rockfalls and debris slides. Most road damages that occurred in Taiwan shared similar terrestrial characteristics to the case study of [27]. Therefore, the repair activity defined in this study is excavation work for rockfall and debris slides in the partial damage condition level. Based on the four aforementioned phases of disaster management, post disaster repair scheduling can be divided into two types: long-term recovery for restoring the whole road network performance and short-term recovery to restore the roadway functionalities in order to support the relief distribution in terms of emergency repair [10; 16]. [PERSON] et al. [28] confirmed in the pre-event of a disaster, road network performance is in a normal condition. When the disaster event occurs, the road network's performance suddenly drops into an unserviceable condition, until the post disaster confusion phase ends. Following the post disaster confusion phase, the response stage performs emergency repair to recover the road network to a minimally serviceable condition for relief distribution and other humanitarian activities. The recovery phase started simultaneously with the response phase after the post disaster event until the road network's performance returned to a normal condition. This study deals with the issues of short-term emergency repair. The maximum target time for the emergency response period after a disaster is in three days [29] and more time can be in seven days depending on the scale of the event [28]. Thus, the challenge of establishing a reliable emergency resource schedule (ERS) to recover the functionalities of the road network is receiving great attention from academics as well as public sectors. In the past decade, there were several studies proposed for road network repair schedules and logistic relief distribution for emergency response phases in post disaster recovery. Most studies employed the Vehicle Routing Problem (VRP) approach to solve the emergency repair scheduling problem. [PERSON] et al. [30] developed an optimization model that was based on the traveling salesman problem (TS) and VRP utilizing Mixed Integer Programming (MIP) that minimizes the maximum arrival time and the average arrival time of delivery relief logistics to the disaster area. [PERSON] et al. [19] solved pickups and delivery problems as an extension of classical VRP to plan the last mile of the relief distribution chain. A multi-stage mixed-integer programming approach was deployed to avoid delays in the delivery of time-critical relief logistics. [PERSON] et al. [31] developed an Assessment Routing Problem (ARP) model based on VRP concepts to minimize the sum of arrival times of distribution relief at the affected communities, by applying the tabu search heuristic algorithm. Another VRP approach was proposed by [PERSON] et al. [32] to select vehicle routes and vehicle quantity based on the active distribution center and the relief demand in each disaster point. This optimization model was solved with a hybrid genetic algorithm (GA).