Control aspects in humanitarian logistics

Fernandez, Thomas E.; Suthikarnnarunai, Nanthi

doi:10.1504/ijlsm.2017.086943

Cited by 2 publications

(2 citation statements)

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“…In contrast to commercial logistics (CL), the main focus of HL is to save lives and provide beneficiaries with aid instead of maximizing profits. However, due to this characteristic, HL has disadvantages when compared to CL as it faces lower technology, challenging inventory control, unstable demand patterns, zero lead time, and unpredictable supply resources [13,14].…”

Section: Introductionmentioning

confidence: 99%

“…Hence, different strategies have been developed within the field of HL for the optimal operation of all the aspects of the supply chain (SC) for the delivery of goods to affected communities considering these disadvantages. In this context, humanitarian relief organizations (HRO) have been identified as the best suited organizations for preparedness and recovery when compared to commercial and military organizations [13]. An important aspect of preparedness is the prepositioning of inventories or warehouses for postdisaster relief.…”

Section: Introductionmentioning

confidence: 99%

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Extended GRASP-Capacitated K-Means Clustering Algorithm to Establish Humanitarian Support Centers in Large Regions at Risk in Mexico

Caballero‐Morales

Barojas-Payán

Sánchez‐Partida

et al. 2018

Journal of Optimization

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Mexico is located within the so-called Fire Belt which makes it susceptible to earthquakes. In fact, two-thirds of the Mexican territory have a significant seismic risk. On the other hand, the country’s location in the tropical zone makes it susceptible to hurricanes which are generated in both the Pacific and Atlantic Oceans. Due to these situations, each year many communities are affected by diverse natural disasters in Mexico and efficient logistic systems are required to provide prompt support. This work is aimed at providing an efficient metaheuristic to determine the most appropriate location for support centers in the State of Veracruz, which is one of the most affected regions in Mexico. The metaheuristic is based on the K-Means Clustering (KMC) algorithm which is extended to integrate (a) the associated capacity restrictions of the support centers, (b) a micro Genetic Algorithm μGA to estimate a search interval for the most suitable number of support centers, (c) variable number of assigned elements to centers in order to add flexibility to the assignation task, and (d) random-based decision model to further improve the final assignments. These extensions on the KMC algorithm led to the GRASP-Capacitated K-Means Clustering (GRASP-CKMC) algorithm which was able to provide very suitable solutions for the establishment of 260 support centers for 3837 communities at risk in Veracruz, Mexico. Validation of the GRASP-CKMC algorithm was performed with well-known test instances and metaheuristics. The validation supported its suitability as alternative to standard metaheuristics such as Capacitated K-Means (CKM), Genetic Algorithms (GA), and Variable Neighborhood Search (VNS).

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extended GRASP-Capacitated K-Means Clustering Algorithm to Establish Humanitarian Support Centers in Large Regions at Risk in Mexico

Caballero‐Morales

Barojas-Payán

Sánchez‐Partida

et al. 2018

Journal of Optimization

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A Decision Support Model for Barriers and Optimal Strategy Design in Sustainable Humanitarian Supply Chain Management

Chowdhury,

Paul,

Khan

et al. 2024

Glob J Flex Syst Manag

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Sustainable humanitarian supply chain (SHSC) management enables effective and efficient responses to natural and human-made disasters. Existing literature falls short of offering decision support (DS) models to address the barriers and strategies to designing SHSC. To this end, this study develops a DS model that identifies and prioritizes the barriers to SHSC and determines optimal strategies for mitigating those barriers. This study adopted both qualitative and quantitative approaches. As part of the qualitative approach, a field study was applied using in-depth interviews to determine the barriers and corresponding strategies, while under the quantitative approach, a quality function deployment (QFD) integrated optimization technique was used to prioritize barriers and determine optimal strategies to mitigate the SHSC barriers. The study found that a lack of contingency planning, the prevalence of corruption and political interference, and a lack of social and environmental awareness are the most important barriers, while logistics outsourcing, supply chain (SC) performance management, and SC flexibility are the most essential strategies. We also found that our DS model is highly flexible and can be adapted under different scenarios, which makes the model applicable to different contexts. This study has a significant contribution to literature and practice. We developed a novel decision model that captured cost savings and leveraged both cost and time savings from interrelated strategies to determine the best optimal strategy while applying QFD-integrated optimization modeling. The paper’s findings will assist humanitarian SC managers in designing an effective, efficient, and sustainable humanitarian SC.

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Control aspects in humanitarian logistics

Cited by 2 publications

References 0 publications

Extended GRASP-Capacitated K-Means Clustering Algorithm to Establish Humanitarian Support Centers in Large Regions at Risk in Mexico

Extended GRASP-Capacitated K-Means Clustering Algorithm to Establish Humanitarian Support Centers in Large Regions at Risk in Mexico

A Decision Support Model for Barriers and Optimal Strategy Design in Sustainable Humanitarian Supply Chain Management

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