Shelter site location under multi-hazard scenarios

Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations

“…Uncertain parameter Fiedrich et al (2000) Survival rates (E), Occurrence of secondary disasters (W), Survival rate of casualties without treatment (S-shaped) Chen and Miller-Hooks (2012) Casualty flows (G), Service times (G), Travel times (G) Haghi et al (2017) Operational costs (S), Commodity demands (S), Casualty flows (S), Failure of health centers (S) Karatas et al (2017) Inter-incident times (E), Weather condition (S), Helicopter failure (S) Mahootchi and Golmohammadi (2018) Link capacities (S), Commodity demands (S), Operational costs (S) Safaei et al (2018) Commodity demands (S) Doan and Shaw (2019) Potential simultaneous disaster happenings (S) Ghasemi et al (2019) Establishment and operational costs (S), Commodity demands (S), Casualty flows (S), Capacities (S) Li and Chung (2019) Travel times (S), Demands (S) Commodity demands/supplies (I), Casualty flows (I), Capacities (I) Ozbay et al (2019) Casualty flows (S) Paul and Zhang (2019) Casualty flows (S), Undamaged supplies (S), Transport cost and time (S), Travel times (E), Truck's travel times (GM) Zhu et al (2019) Deprivation cost (Author-defined) E: Exponential, W: Weibull, G: General, S: Scenario-based, I: Interval, GM: Gamma Reference Dynamic parameter/Information update mechanism * Fiedrich et al (2000) Finished/started affected sites, Set of depots, New affected sites due to secondary disasters, Destroyed affected sites/links 2019) proposed a partially observable Markov decision process for the routing of UAVs to search for casualties at affected sites. The vehicles' path planning was formulated to assign higher priorities to sites that are more likely to have casualties.…”

An efficiency-based interval type-2 fuzzy multi-criteria group decision making for makeshift hospital selection

“… [4] investigated a multi-criteria group decision making (MCGDM) method and applied it to locate makeshift (Fangcang) hospitals, they overlooked the upper and lower heights of TrIT2FSs. Considering that Fangcang hospital is also a special form of emergency shelters, some studies [48] , [49] , [50] , [51] , [52] concerning the site selection of emergency shelters are also reviewed. These studies mainly focused on the location of emergency shelters for post-natural disaster rescue operations.…”

“…These studies mainly focused on the location of emergency shelters for post-natural disaster rescue operations. It is evident that natural disaster emergencies are quite different from public health emergencies, which implies that methods [48] , [49] , [50] , [51] , [52] are not suitable for solving the FHL problem in this paper. In recent years, BWM [12] , [40] has become an effective and popular tool to determine the weights of criteria.…”

A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information

“…Ozbay et al. (2019) develop a three‐stage stochastic mixed‐integer programming model to locate shelter sites and allocate victims to shelter sites under multi‐hazard scenarios. Paul and Zhang (2019) develop a two‐stage stochastic programming model to formulate the hurricane preparedness problem.…”

“…To this end, many studies have investigated the reliable location model to handle facility disruption (Cui et al., 2010; Ghavamifar et al., 2018; Afify et al., 2019; Hoseinpour and Ahmadijavid, 2019). And the previous works do not pay attention to the strategic nature of terrorist attacks (Snyder and Daskin, 2005; Jia et al., 2007; Alizadeh et al., 2019; Ozbay et al., 2019). However, terrorist events differ from natural ones in that they are launched by an attacker who can adjust their strategies to circumvent possible defense actions, according to Berman and Gavious (2007).…”