In healthcare organizations, medical staff scheduling is vital to achieving optimal patient care, ensuring the well-being of medical officers, and the efficiency of operations. This research aims to address the challenges of optimizing the scheduling of limited resources for multiple projects for medical staff, through a comparative analysis of Google OR tools and genetic algorithms. We evaluate the performance of these tools in various scenarios, taking into account factors such as overtime, work balance, and scheduling efficiency. This comparative analysis reveals the strengths and weaknesses of each approach, facilitating the development of improved medical staff scheduling solutions. Additionally, we offer algorithmic optimizations tailored to meet the requirements of specific healthcare settings, which contribute to enhancing the adaptability and effectiveness of scheduling tools. The research findings provide valuable insights to guide decision-making in healthcare institutions, ultimately aiming to enhance the quality of care provided by medical officers and improve the overall efficiency of the healthcare system. In conclusion, the results show that the modified Google OR algorithm significantly outperforms the Google OR tools and the regular genetic algorithm in performance.
Medical officer scheduling Multi-project resource-constrained scheduling Genetic algorithms Google OR Tools Algorithm comparison.
Primary Language | English |
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Subjects | Software Engineering (Other) |
Journal Section | Research Article |
Authors | |
Early Pub Date | April 26, 2024 |
Publication Date | April 30, 2024 |
Submission Date | January 5, 2024 |
Acceptance Date | April 4, 2024 |
Published in Issue | Year 2024 Volume: 8 Issue: 1 |
International Journal of 3D Printing Technologies and Digital Industry is lisenced under Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı