Capacitated Location-Allocation Model for Emergency Supply Chain: The Case of Morocco

Abstract: Recently, Morocco has experienced a series of disasters, including the El Haouz earthquake in 2023, which have brought renewed attention to the country’s emergency preparedness and the efficiency of its national emergency supply chain. In addition, this study considers a prospective scenario based on potential flood events in northern Morocco to evaluate future resilience requirements. In this context, improving the strategic planning of Emergency Supply Facilities (ESFs) is essential for strengthening disaster response capabilities. This study develops a capacitated location–allocation optimization model for emergency supply chain planning that incorporates demand uncertainty, flexible allocation of ESFs, and donor contributions. The proposed framework is evaluated through computational experiments using problem instances consisting of multiple candidate ESF locations, demand points, and disruption scenarios, allowing the analysis of different emergency response configurations. The results indicate that the proposed optimization framework can significantly improve the efficiency and responsiveness of Morocco’s emergency supply chain. The model provides a practical decision-support tool for policymakers and planners to enhance disaster preparedness and resource allocation in national emergency logistics systems.

Imane Sassaoui, Aziz Ait Bassou, Mustapha Hlyal and Jamila El Alami. “Capacitated Location-Allocation Model for Emergency Supply Chain: The Case of Morocco”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.3 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170316

@article{Sassaoui2026,
title = {Capacitated Location-Allocation Model for Emergency Supply Chain: The Case of Morocco},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170316},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170316},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {3},
author = {Imane Sassaoui and Aziz Ait Bassou and Mustapha Hlyal and Jamila El Alami}
}