Relief operations as a multi-project: Colombian case

Forero, María Catalina González; Rodríguez, Leonardo José González

doi:10.5267/j.ijiec.2019.5.002

Cited by 4 publications

(1 citation statement)

References 40 publications

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“…PRED is also different from other methods, such as EMPROV, which are designed to support improvised decision-making [72] because they assume the data are available and do not provide frameworks for predicting the unavailable data, such as fatalities during the disaster response. The method of pattern finding in this study is, to some extent, similar to rule-based clustering used for prediction in various studies [72,73]. However, it is unique in a sense that it uses the available data to predict the impact in the early hours of disaster strike, with no real-time data drawn from the area.…”

Section: Conclusion Contributions and Limitationsmentioning

confidence: 99%

A Rule-Based Predictive Model for Estimating Human Impact Data in Natural Onset Disasters—The Case of a PRED Model

Rye

Aktaş

2023

Logistics

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Background: This paper proposes a framework to cope with the lack of data at the time of a disaster by employing predictive models. The framework can be used for disaster human impact assessment based on the socio-economic characteristics of the affected countries. Methods: A panel data of 4252 natural onset disasters between 1980 to 2020 is processed through concept drift phenomenon and rule-based classifiers, namely the Moving Average (MA). Results: Predictive model for Estimating Data (PRED) is developed as a decision-making platform based on the Disaster Severity Analysis (DSA) Technique. Conclusions: comparison with the real data shows that the platform can predict the human impact of a disaster (fatality, injured, homeless) with up to 3% error; thus, it is able to inform the selection of disaster relief partners for various disaster scenarios.

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Section: Conclusion Contributions and Limitationsmentioning

confidence: 99%

A Rule-Based Predictive Model for Estimating Human Impact Data in Natural Onset Disasters—The Case of a PRED Model

Rye

Aktaş

2023

Logistics

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Emergent strategy and cascading behaviour patterns during crises: evidence from Brisbane’s 2011 floods

Yezdani

Sanzogni

Houghton

2022

Australasian Journal of Environmental Management

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Development of an Efficient Framework for the Distribution of Essential Relief Materials during Floods by Clustering Technique

Sudeesh

Rameshkumar

Anbuudayasankar

2021

IOP Conf. Ser.: Mater. Sci. Eng.

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An efficient logistic network is extremely vital to distribute essential items quickly to the region wherever the natural calamities have occurred. This paper focuses on developing an efficient framework for the distribution of essential relief materials to the people in Kuttanad Taluk of Alappuzha District in Kerala, India during the monsoon season. The existing relief distribution network in the flood-affected region has been studied in detail and an improved distribution logistics has been suggested in this study. K-means clustering algorithm has been used to identify the location for the relief material distribution centres in the flood-affected region. The proposed approach reduces the efforts needed to coordinate the relief activities by optimally identifying no. of distribution centres and locations of distribution centres with an objective of reducing the total supply chain transportation distance for the supply of essential items during the flood. The proposed clustering approach reduces the traveling distance of the people during the flood to receive the relief material to an extent of 88%.

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Relief operations as a multi-project: Colombian case

Cited by 4 publications

References 40 publications

A Rule-Based Predictive Model for Estimating Human Impact Data in Natural Onset Disasters—The Case of a PRED Model

A Rule-Based Predictive Model for Estimating Human Impact Data in Natural Onset Disasters—The Case of a PRED Model

Emergent strategy and cascading behaviour patterns during crises: evidence from Brisbane’s 2011 floods

Development of an Efficient Framework for the Distribution of Essential Relief Materials during Floods by Clustering Technique

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