Relief Demand Calculation in Humanitarian Logistics Using Material Classification

Shao, Jianfang; Liang, Changyong; Xi-hui, Wang; Liang, Liang

doi:10.3390/ijerph17020582

Cited by 9 publications

(5 citation statements)

References 45 publications

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“…Previous studies on demand calculation mainly focus on demand forecasting methodology, with many neglecting the checklist of critical supplies and practical background [ 4 ]. Models for the distribution of relief supplies often assume their immediate availability upon the occurrence of a natural disaster.…”

Section: Discussionmentioning

confidence: 99%

“…The most heavily criticized aspect of official responses is often one of inefficient relief effort that does not punctually deliver the critical supplies needed to disaster-hit areas. How to respond to such emergencies in the most efficient manner in order to minimize the loss of life and maximize the efficiency of the rescue operations is the ultimate aim of disaster relief [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

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A Quantitative Study on Crucial Food Supplies after the 2011 Tohoku Earthquake Based on Time Series Analysis

Zhu

Wang

Regan

et al. 2020

IJERPH

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Awareness of the requested quantity and characteristics of emergency supplies is crucial for facilitating an efficient relief operation. With the aim of focusing on the quantitative study of immediate food supplies, this article estimates the numerical autoregressive integrative moving average (ARIMA) model based on the actual data of 14 key commodities in the Sendai City of Japan during the 2011 Tohoku earthquake. Although the temporal patterns of key food commodity groups are qualitatively similar, the results show that they follow different ARIMA processes, with different autoregressive moving averages and difference order patterns. A key finding is that 3 of the 14 items are significantly related to the number of temporary residents in shelters, revealing that the relatively low number of different items makes it easier to deploy these key supplies or develop regional purchase agreements so as to promptly obtain them from distributors.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Quantitative Study on Crucial Food Supplies after the 2011 Tohoku Earthquake Based on Time Series Analysis

Zhu

Wang

Regan

et al. 2020

IJERPH

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“…For both Pueblo Rico and Dosquebradas, although the risk mitigation recipes may be similar, the results (Figures 8-13) suggest that there is a need for specific materials according to the aftermath of disasters (Shao et al, 2020). Regarding floods, households may suffer from physical damage, but people's lives may be hardly exposed.…”

Section: Logistic Maximum-entropy Regressionmentioning

confidence: 96%

An entropy-based approach for disaster risk assessment and humanitarian logistics operations planning in Colombia

Rentería

Chong

Brito

et al. 2021

JHLSCM

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PurposeThis paper aims to design a vulnerability assessment model considering the multidimensional and systematic approach to disaster risk and vulnerability. This model serves to both risk mitigation and disaster preparedness phases of humanitarian logistics.Design/methodology/approachA survey of 27,218 households in Pueblo Rico and Dosquebradas was conducted to obtain information about disaster risk for landslides, floods and collapses. We adopted a cross entropy-based approach for the measure of disaster vulnerability (Kullback–Leibler divergence), and a maximum-entropy estimation for the reconstruction of risk a priori categorization (logistic regression). The capabilities approach of Sen supported theoretically our multidimensional assessment of disaster vulnerability.FindingsDisaster vulnerability is shaped by economic, such as physical attributes of households, and health indicators, which are in specific morbidity indicators that seem to affect vulnerability outputs. Vulnerability is heterogeneous between communities/districts according to formal comparisons of Kullback–Leibler divergence. Nor social dimension, neither chronic illness indicators seem to shape vulnerability, at least for Pueblo Rico and Dosquebradas.Research limitations/implicationsThe results need a qualitative or case study validation at the community/district level.Practical implicationsWe discuss how risk mitigation policies and disaster preparedness strategies can be driven by empirical results. For example, the type of stock to preposition can vary according to the disaster or the kind of alternative policies that can be formulated on the basis of the strong relationship between morbidity and disaster risk.Originality/valueEntropy-based metrics are not widely used in humanitarian logistics literature, as well as empirical data-driven techniques.

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“…They considered the uncertain budget and conducted a case study for floods and landslides in Rio de Janeiro State, Brazil, by a two-phase heuristic. Jianfang Shao [35] proposed a model for calculating the demand for relief in multiple disasters, and their proposed model is divided into two parts: supply classification and demand calculation.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust Design of Relief Distribution Networks Considering Uncertainty

Nayeem

Lee

2021

Sustainability

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In the post-disaster response phase, an efficient relief distribution strategy plays a vital role in alleviating suffering in disaster-stricken areas, which sometimes becomes challenging in humanitarian logistics. Most governments pre-located the relief goods at the pre-determined warehouses against possible disasters. Those goods must be shipped to the relief distribution centers (RDCs) to be further distributed to the victims in impacted areas upon the disasters. Secondary disasters can occur due to the first disaster and can occur relatively close in time and location, resulting in more suffering and making the relief distribution activities more challenging. The needs of additional RDCs must be determined as well in response to the secondary disasters. A robust optimization model is proposed to hedge against uncertainties in RDCs’ capacity and relief demand. Its objective is to minimize the sum of transportation cost, additional RDC cost, and shortage of commodities. The computational results are given to demonstrate the effectiveness of the proposed model. The sensitivity analysis gives an insight to the decision-makers.

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Relief Demand Calculation in Humanitarian Logistics Using Material Classification

Cited by 9 publications

References 45 publications

A Quantitative Study on Crucial Food Supplies after the 2011 Tohoku Earthquake Based on Time Series Analysis

A Quantitative Study on Crucial Food Supplies after the 2011 Tohoku Earthquake Based on Time Series Analysis

An entropy-based approach for disaster risk assessment and humanitarian logistics operations planning in Colombia

Robust Design of Relief Distribution Networks Considering Uncertainty

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