Transportation model of humanitarian logistics: case of COVID-19 monsoon floods
Yudi Fernando,
Muhammad Shabir Shaharudin,
Umi Nadhira Abdul Majid and
Imran Syamil Zahanapi
International Journal of Business Innovation and Research, 2024, vol. 33, issue 3, 346-367
Abstract:
It is a challenging task to manage humanitarian logistics during COVID-19. This paper investigates how firms overcome floods and the COVID-19 pandemic transportation model simultaneously due to its severity on firms' performance. This paper aims to examine the transportation model's optimism, which needs to select the best route to deliver the monsoon floods relief operations during the COVID-19 pandemic. Arena software with a discrete event simulation and a multilayer perceptron (MLP) analysis using a deep learning technique was deployed in the method. The simulation software shows the most effective scenario with flexibility and MLP with root relative squared results found that disaster operations for mitigation are the most critical humanitarian performance indicators. The humanitarian logistics model is practical for NGOs or government agencies since it was designed with the COVID-19 scenario. The simulation technique is suitable for solving a practical problem and providing an alternative solution to humanitarian logistics.
Keywords: transportation model; discrete event; simulation; non-government organisation; humanitarian logistics; multilayer perceptron; MLP; deep learning; COVID-19. (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbire:v:33:y:2024:i:3:p:346-367
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