Document Type : Original Research Paper
Authors
Geospatial Information Systems Department, Faculty of Surveying Engineering, K. N.Toosi University of Technology, Tehran, Iran
Abstract
Background and Objectives: Optimal management of humanitarian supply chains and distribution of relief items after natural disasters is a major challenge in the field of crisis management. Despite the importance of optimal allocation of local distribution centers in post-disaster situations, many existing decision-making tools lack spatial capabilities, flexibility in scenario building, and ease of access. Aiming to fill the gap in previous studies, this paper designs a web-based system that utilizes geographic information systems (GIS) and meta-heuristic algorithms to enable optimal allocation of distribution centers and management of relief items.
Methods: In this study, an intelligent web-based spatial decision support system has been developed that helps decision makers allocate relief distribution centers more efficiently in different post-crisis scenarios. This system consists of three main parts, including a database, a decision engine, and a web-based user interface, and can be fully implemented in a browser without the need to install additional software. Also, genetic and forbidden search algorithms have been integrated to optimize resource allocation and distribution of relief items in this system. Users can edit input data, define different scenarios, and visually view the results on a map. In this system, common uncertainties after disasters, including different rates of affected populations, as well as five different planning periods ranging from 8 to 72 hours (i.e. 8, 16, 24, 48, and 72 hours), have been considered. The system's high flexibility in defining and analyzing various scenarios makes it an effective tool for improving decision-making in planning relief aid distribution operations.
Findings: Results show that the proposed hybrid algorithm has been able to improve the optimal allocation of distribution centers and the effective distribution of items and reduce the amount of unmet demand. However, depending on the number of iterations of the algorithm, different scenarios, and some input parameters, the results have sometimes been unstable, which can be investigated and analyzed more precisely in future studies.
Conclusion: This study presents a comprehensive, web-based decision support system for the optimal management of relief distribution, which can significantly increase the efficiency of crisis operations. The combined use of meta-heuristic algorithms and geographic data in this system enables rapid response and accurate decision-making. Future development and improvements of this system can include support for different types of items and diverse disaster situations to play a more effective role in reducing human and financial losses.
Keywords
- Spatial Decision-Support System
- Distribution of Relief-Items
- Web-based System
- Disaster Management
- Genetics and Tabu Algorithms
Main Subjects
COPYRIGHTS
© 2025 The Author(s). This is an open-access article distributed under the terms and conditions of the Creative Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
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