Proceedings of the International Conference on Decision Aid and Artificial Intelligence (ICODAI 2024)

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Combining Unsupervised Learning with the Genetic Algorithm for the Blood Delivery Problem

Authors
Abdelmalek Belhadj1, *, Hajer Ben-Romdhane1
1Université de Tunis, ISG de Tunis, LARODEC, Tunis, Tunisia
*Corresponding author. Email: malekbelhadj61@gmail.com
Corresponding Author
Abdelmalek Belhadj
Available Online 24 February 2025.
DOI
10.2991/978-94-6463-654-3_15How to use a DOI?
Keywords
Blood delivery problem; optimization; DBSCAN algorithm; genetic algorithm
Abstract

Efficient and timely distribution of blood is crucial for ensuring that patients receive the necessary medical treatments within critical timeframes. Delays in blood delivery can significantly impact patient outcomes, as prompt availability of blood products is essential for effective medical care. This study introduces a novel hybrid approach that combines Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to optimize the routing of blood deliveries. By using DBSCAN to group delivery locations based on spatial proximity and operational constraints, the complexity of the distribution challenge is reduced. The GA then fine-tunes the routes within these clusters, aiming to minimize travel distance and meet the stringent timing requirements essential for effective blood delivery. Experimental results highlight the improved efficiency and reliability of the proposed method, demonstrating its potential to enhance blood distribution logistics and ensure timely patient care.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Decision Aid and Artificial Intelligence (ICODAI 2024)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
24 February 2025
ISBN
978-94-6463-654-3
ISSN
2589-4919
DOI
10.2991/978-94-6463-654-3_15How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Abdelmalek Belhadj
AU  - Hajer Ben-Romdhane
PY  - 2025
DA  - 2025/02/24
TI  - Combining Unsupervised Learning with the Genetic Algorithm for the Blood Delivery Problem
BT  - Proceedings of the  International Conference on Decision Aid and Artificial Intelligence (ICODAI 2024)
PB  - Atlantis Press
SP  - 186
EP  - 199
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-654-3_15
DO  - 10.2991/978-94-6463-654-3_15
ID  - Belhadj2025
ER  -