Shelter location and transportation planning under hurricane conditions

Li, Anna C. Y.; Nozick, Linda K.; Xu, Ningxiong; Davidson, Rachel A.

doi:10.1016/j.tre.2011.12.004

Cited by 177 publications

(106 citation statements)

References 36 publications

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“…Murali et al [18] formulate a special case of the coverage model using a loss function and chance-constraints. The basic FLMs also can be extended to complex optimization models, including models based on bi-level optimization [19,20], hierarchical models [21], and models that account for dynamic environments [22].…”

Section: Shelter Site Locationmentioning

confidence: 99%

Planning Emergency Shelters for Urban Disaster Resilience: An Integrated Location-Allocation Modeling Approach

Zhao

Sun

et al. 2017

Sustainability

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Abstract:In recent years, extreme natural hazards threaten cities more than ever due to contemporary society's high vulnerability in cities. Hence, local governments need to implement risk mitigation and disaster operation management to enhance disaster resilience in cities. Transforming existing open spaces within cities into emergency shelters is an effective method of providing essential life support and an agent of recovery in the wake of disasters. Emergency shelters planning must identify suitable locations for shelters and reasonably allocate evacuees to those shelters. In this paper, we first consider both the buildings' post-disaster condition and the human choice factor that affect evacuees' decision, and propose a forecasting method to estimate the time-varying shelter demand. Then we formulate an integrated location-allocation model that is used sequentially: an emergency shelter location model to satisfy the time-varying shelter demand in a given urban area with a goal of minimizing the total setup cost of locating the shelters and an allocation model that allocates the evacuees to shelters with a goal of minimizing their total evacuation distance. We also develop an efficient algorithm to solve the model. Finally, we propose an emergency shelters planning based on a case study of Shanghai, China.

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Section: Shelter Site Locationmentioning

confidence: 99%

Planning Emergency Shelters for Urban Disaster Resilience: An Integrated Location-Allocation Modeling Approach

Zhao

Sun

et al. 2017

Sustainability

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“…Although, real-time location-allocation and routing of late evacuees to shelters are subject to a range of other objectives, including capacities, distances, and susceptibility or vulnerability to the disaster, which should also be simultaneously optimised while operating within a range of stringent constraints. (Li et al 2012;Negreiros and Palhano 2006). Nevertheless, the most challenging objective of emergency situation management is cited as the quick and safe transportation of late evacuees to shelters within a very tight time window.…”

Section: Multi-objective Decision Analyticsmentioning

confidence: 99%

“…Real-time assignment of evacuees to a shelter is affected by a range of factors, including its capacity, distance, and susceptibility or vulnerability to the hazard (Li et al 2012;Negreiros and Palhano 2006). Furthermore, other objectives should also be simultaneously optimised while operating within a range of constraints.…”

Section: Multi-objective Decision Analyticsmentioning

confidence: 99%

Multi-Objective Decision Analytics for Short-Notice Bushfire Evacuation: An Australian Case Study

Shahparvari

Chhetri

Abareshi

et al. 2015

AJIS

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Late evacuation in a bushfire is a crucial stage of emergency response, which requires a quick response under life-threatening conditions. Lack of operational intelligence and decision support system to execute evacuation of residents within a 10 minutes time window were among key factors, which contributed to the loss of 119 lives (68 percent of total fatalities) during the Black Saturday 2009 bushfire in Victoria. Hard constraints of the limited time window, the uncertainty of bushfire spread, road disruptions and elderly and disabled late evacuees pose multiple challenges for fire agencies. An application of analytics and decision support system, capable of computing Just-in-time allocation of resources, can enhance the capacity of fire services agencies. Using the multi-objective analytics, this paper therefore develops optimal resource allocation models to enhance emergency response to improve the efficiency of late evacuation response.Three key operational challenges are tackled including timely evacuation, shelter assignment and routing. Three bushfire scenarios are constructed to incorporate constraints of restricted time-window and potential road disruptions. Capacity and number of rescue vehicles and shelters are other constraints. This mathematical model is solved by the application of theconstraint approach. Objective functions are simultaneously optimised to maximise the total number of evacuees while minimise the number of assigned rescue vehicles and shelters. We argue that this model provides a scenario-based decision-making tool to aid maximise the resource utilisation and coverage of late evacuees. The analytics based insights drawn from various disruption scenarios could help emergency services agencies in identifying appropriate strategies to improve the efficiency of late evacuation response.

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“…Siddiqui et al (2012) [27] and Verma et al (2012) [28] studied the evacuation problem of hazardous materials, in which Siddiqui et al (2012) [27] proposed a computational fluid dynamics-(CFD-) based model for indoor risk assessment that considered accidental release of a sustained, small, undetected leak of a dense toxic gas (chlorine) in an industrial indoor environment. Li et al (2012) [29], Najafi et al (2013) [30], and Bish and Sherali (2013) [31] studied largescale regional evacuations caused by hurricanes, wildfires, or earthquakes. They studied the demand-based strategies of aggregate-level staging and routing to structure the evacuation demand, both with and without congestion and then designed two heuristics.…”

Section: Introductionmentioning

confidence: 99%

Emergency Evacuation of Hazardous Chemical Accidents Based on Diffusion Simulation

et al. 2017

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The recent rapid development of information technology, such as sensing technology, communications technology, and database, allows us to use simulation experiments for analyzing serious accidents caused by hazardous chemicals. Due to the toxicity and diffusion of hazardous chemicals, these accidents often lead to not only severe consequences and economic losses, but also traffic jams at the same time. Emergency evacuation after hazardous chemical accidents is an effective means to reduce the loss of life and property and to smoothly resume the transport network as soon as possible. This paper considers the dynamic changes of the hazardous chemicals' concentration after their leakage and simulates the diffusion process. Based on the characteristics of emergency evacuation of hazardous chemical accidents, we build a mixed-integer programming model and design a heuristic algorithm using network optimization and diffusion simulation (hereafter NODS). We then verify the validity and feasibility of the algorithm using Jinan, China, as a computational example. In the end, we compare the results from different scenarios to explore the key factors affecting the effectiveness of the evacuation process.

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Shelter location and transportation planning under hurricane conditions

Cited by 177 publications

References 36 publications

Planning Emergency Shelters for Urban Disaster Resilience: An Integrated Location-Allocation Modeling Approach

Planning Emergency Shelters for Urban Disaster Resilience: An Integrated Location-Allocation Modeling Approach

Multi-Objective Decision Analytics for Short-Notice Bushfire Evacuation: An Australian Case Study

Emergency Evacuation of Hazardous Chemical Accidents Based on Diffusion Simulation

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