Title: Transportation model of humanitarian logistics: case of COVID-19 monsoon floods

Authors: Yudi Fernando; Muhammad Shabir Shaharudin; Umi Nadhira Abdul Majid; Imran Syamil Zahanapi

Addresses: Faculty of Industrial Management, Universiti Malaysia Pahang, Malaysia; Management Department, BINUS Online Learning, Bina Nusantara University, Indonesia ' Faculty of Industrial Management, Universiti Malaysia Pahang, Malaysia ' Faculty of Industrial Management, Universiti Malaysia Pahang, Malaysia ' Faculty of Industrial Management, Universiti Malaysia Pahang, Malaysia

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.

DOI: 10.1504/IJBIR.2024.137271

International Journal of Business Innovation and Research, 2024 Vol.33 No.3, pp.346 - 367

Received: 07 Apr 2021
Accepted: 15 Jun 2021
Published online: 11 Mar 2024 *

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