Integrating Stochastic Failure of Road Network and Road Recovery Strategy into Planning of Goods Distribution after a Large-Scale Earthquake

Abstract

Disaster relief operations are complex and can benefit greatly from a high level of preparedness. One of the main sources of complexity in disaster operations is uncertainty. An analysis of a disaster relief operation in Aichi Prefecture, Japan, preparing for the periodic Tokai–Tonankai earthquake is presented. In this study, the possible degradation of the road network is considered by including a stochastic element to represent the possibility of link failure dependent on earthquake intensity in each subregion. Also, a strategy to fix the roads is integrated into the analysis to evaluate its impact on the disaster logistics operations. The analysis is performed with the current road network of Aichi Prefecture. The results suggest the best preparation of resources and identify vulnerable destinations that are most likely to be cut off by the disaster. Also analyzed is a relocation of hubs that can reduce the total response time and take into account the possibility that some links will be destroyed. This analysis is important to help planners to evaluate their strategies, to identify vulnerable locations, and to be able to prepare in advance the best methods to deal with the uncertainty of road failure.

Modeling the Effectiveness of Infrastructure and Travel Demand Management Measures to Improve Traffic Congestion during Typhoons

“…Although road segments can partially fail (i.e., obstruction of only part of road width), this type of failure is nearly impossible to predict, and during a disaster, it is more likely that the constraint on the capacity of the road network is whether or not a link is usable ( 32 , 33 ). The failure probability of a link is obtained using a negative exponential distribution, similar to the works by Kroger and Zio ( 34 ) and Wisetjindawat et al ( 35 ). The probability that link i fails is defined as follow:…”

A Mathematical Pre-Disaster Model with Uncertainty and Multiple Criteria for Facility Location and Network Fortification

“…To the best of the authors' knowledge, the first model to consider the coordination of the activities of relief transportation, road recovery, and inventory prepositioning is by Wisetjindawat et al [15]. The authors consider ongoing road repairs as constraints on the availability of roads, rather than as part of the decision making process, i.e., all links in the transportation network must be available after 24 h. Therefore, the problem is formulated as a location-routing problem that explicitly consider routes that satisfy the availability time constraint, at a given confidence level.…”

Pre-positioning of relief items under road/facility vulnerability with concurrent restoration and relief transportation

“…Disregarding Wisetjindawat et al (2015), all studies in Table 1 incorporate the uncertainty in relief demand and/or supply. Furthermore, almost all of the papers involve the uncertainty in at least one of travel time, transportation cost, or road capacity as well.…”

“…As noted by C ¸elik (2016), in communities where road recovery and relief transportation are managed or coordinated by the same entity (such as the local municipality of a region), integrated planning and scheduling of these activities may lead to significant improvements in the timeliness of the deliveries, which is also applicable to the case of inventory pre-positioning. To the best of our knowledge, only one study (Wisetjindawat et al, 2015) in the pre-positioning literature considers the coordination of the efforts in these two activities, but does so only by considering ongoing road repair as constraints on the availability of roads, rather than as part of the decision making mechanism. Hence, even though road vulnerability has been included in the design of humanitarian relief pre-positioning networks, there exists an important gap in the literature on the incorporation of road recovery into the network design process.…”