A decision support system for post-disaster interim housing

Rakes, Terry R.; Deane, Jason K.; Rees, Loren Paul; Fetter, Gary

doi:10.1016/j.dss.2014.06.012

Cited by 32 publications

(14 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Many quantitative studies have measured postdisaster housing recovery (or restoration) using improvement value data (Hamideh, 2015; Hamideh et al., 2018), permit data (Lester, Perry, & Moynihan, 2014; Stevenson, Emrich, Mitchell, & Cutter, 2010), or postdisaster aerial imagery of structures (Hoshi, Murao, Yoshino, Yamazaki, & Estrada, 2014) as proxy measures. Few probabilistic or predictive models exist for housing recovery including optimizing recovery outcomes from various temporary housing solutions (El‐Anwar, 2010; El‐Anwar, El‐Rayes, & Elnashai, 2010), a decision support system for assigning families to temporary housing units and locations (Rakes, Deane, Rees, & Fetter, 2014), an agent based model of household‐based decisions to rebuild (Nejat & Damnjanovic, 2012), a least absolute shrinkage and selection operator model on household decision making (Nejat & Ghosh, 2016), material resource system dynamics model on construction material supply (Diaz, Kumar, & Behr, 2015) and labor supply (Kumar, Diaz, Behr, & Toba, 2015) for rebuilding housing, and a Markov chain model for building functionality restoration that was designed generically, but could be applied to housing functionality restoration (Lin & Wang, 2017). Most of these studies focus on the physical process of rebuilding, and on recovery of houses, as opposed to recovery of households.…”

Section: Existing Recovery Modelsmentioning

confidence: 99%

Postdisaster Housing Stages: A Markov Chain Approach to Model Sequences and Duration Based on Social Vulnerability

Sutley

Hamideh

2020

Risk Analysis

View full text Add to dashboard Cite

Housing recovery is an unequal and complex process presumed to occur in four stages: emergency shelter, temporary shelter, temporary housing, and permanent housing. This work questions the four-stage typology and examines how different types of shelter align with multiple housing recovery stages given different levels of social vulnerability. This article also presents a Markov chain model of the postdisaster housing recovery process that focuses on the experience of the household. The model predicts the sequence and timing of a household going through housing recovery, capturing households that end in either permanent housing or a fifth possible stage of failure. The probability of a household transitioning through the stages is computed using a transition probability matrix (TPM). The TPM is assembled using proposed transition probability models that vary with the social vulnerability of the household. Monte Carlo techniques are applied to demonstrate the range of sequences and timing that households experience going through the housing recovery process. A set of computational rules are established for sending a household to the fifth stage, representing a household languishing in unstable housing. This predictive model is exemplified on a virtual community, Centerville, where following a severe earthquake scenario, differences in housing recovery times exceed four years. The Centerville analysis results in nearly 5% of households languishing in unstable housing, thereby failing to reach housing recovery. These findings highlight the disparate trajectories experienced by households with different levels of social vulnerability. Recommendations are provided at the end for more equitable postdisaster recovery policies.

show abstract

Section: Existing Recovery Modelsmentioning

confidence: 99%

Postdisaster Housing Stages: A Markov Chain Approach to Model Sequences and Duration Based on Social Vulnerability

Sutley

Hamideh

2020

Risk Analysis

View full text Add to dashboard Cite

show abstract

“…The approach heavily depends on a reliable and updated database of temporary housing alternatives [45]. Rakes et al further expand on occupant-specific needs and assignments to temporary housing units by optimizing the access and proximity to support services [59]. A novel and holistic planning framework is designed to manage expenditure while offering customized housing plans to satisfy these occupant specific social, economic, and psychological needs [60].…”

Section: Resultsmentioning

confidence: 99%

A Review of Temporary Housing Management Modeling: Trends in Design Strategies, Optimization Models, and Decision-Making Methods

Perrucci

Baroud

2020

Sustainability

View full text Add to dashboard Cite

Temporary housing plays a critical role in disaster response and recovery by providing a temporary home for displaced people before they return to their permanent residence. In recent years, temporary housing has faced three primary dilemmas related to design type, site selection, and cost. Significant contributions have been made in research and in practice to improve temporary housing management. However, gaps still exist in resolving the dilemmas, and a critical review and evaluation of current methods is needed to determine the path forward and identify priorities of future research. This paper presents a comprehensive overview of prior methods developed and applied towards temporary housing management and identifies future pathways for success in temporary housing research and implementation. The literature review reveals that temporary housing requires further research in proactive management, storage, sustainability, and community resilience to effectively enhance post-disaster temporary housing. This study finds that programs such as the Leadership in Energy and Environmental Design (LEED) and the Sheltering and Temporary Essential Power (STEP) program provide methodologies which can benefit temporary housing implementation, designs, and modeling. In addition, circular economy thinking can enable the recyclability of temporary housing to reduce economic and environmental impacts.

show abstract

“…Rakes et al aimed to assign the families to temporary houses after the disaster by taking various criteria into account such as education and health, with the help of the decision support system they have developed. Discrete mathematical modelling and heuristic methods were used in the study [6].…”

Section: Literature Surveymentioning

confidence: 99%

Analysis of Permanent Housing Built after Disaster: Van (Turkey)

Öztaş

Akkaya

2019

Teh. vjesn.

View full text Add to dashboard Cite

In 2011, 644 people passed away after two earthquakes struck the city of Van, located in eastern Turkey. Houses collapsed or were rendered uninhabitable. Thousands of people became homeless. In response, the government built 17 489 units of permanent housing in a standard size and type. This study determined a more effective housing allocation for earthquake victims by considering the types of households (one-person households, one-family households, extended-family households and multi-person, no family households) and the total available housing area as allotted by the government's relief building budget. The Analytic Hierarchy Process was used to prioritize home features for each type of household. These results showed that housing size tailored to household need was more important than price, location or design. Mathematical modeling was then used to identify housing space allocations that would serve family needs better than a uniform building approach.

show abstract

A decision support system for post-disaster interim housing

Cited by 32 publications

References 20 publications

Postdisaster Housing Stages: A Markov Chain Approach to Model Sequences and Duration Based on Social Vulnerability

Postdisaster Housing Stages: A Markov Chain Approach to Model Sequences and Duration Based on Social Vulnerability

A Review of Temporary Housing Management Modeling: Trends in Design Strategies, Optimization Models, and Decision-Making Methods

Analysis of Permanent Housing Built after Disaster: Van (Turkey)

Contact Info

Product

Resources

About