Araştırma Makalesi

ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION

Cilt: 8 Sayı: 1 30 Nisan 2024
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ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION

Öz

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.

Anahtar Kelimeler

Kaynakça

  1. 1. Google Corporation, “Google Developers”, http://developers.google.com/, January 9, 2024.
  2. 2. GeeksforGeeks, “Genetic Algorithms”, https://www.geeksforgeeks.org/genetic-algorithms/. January 9, 2024.
  3. 3. Static, U., Jacko, P., & Kirkbride, C., “Performance evaluation of scheduling policies for the dynamic and stochastic resource-constrained multi-project scheduling problem “, International Journal of Production Research, Vol. 60, Issue 4, Pages 1411-1423, 2022.
  4. 4. Browning, T. R., Yassine, A. A., “Resource-constrained multi-project scheduling: Priority rule performance revisited“, International Journal of Production Economics, Vol. 126, Issue 2, Pages 212-228, 2010.
  5. 5. Fischer, F. M., Borges, F. N., Rotenberg, L., Latorre, M. R., Soares, N. S., Rosa, P. L., Teixeira, L. R., Nagai, R., Steluti, J., Landsbergis, P., “Workability of health care shift workers: What matters? “, Chronobiol Int., Vol. 23, Issue 6, Pages 1165-79, 2006.
  6. 6. Mahmud, F., “Evolutionary Algorithms for Resource Constrained Project Scheduling Problems “, Doctoral Thesis, UNSW University, Sydney, 2023.
  7. 7. El-Abbasy, M. S. K., “Multi-objective multi-project construction scheduling optimization“, Doctoral Thesis, Concordia University, Montreal, 2015.
  8. 8. Chen, R., Liang, C., Gu, D., Leung, J. Y., “A multi-objective model for multi-project scheduling and multi-skilled staff assignment for IT product development considering competency evolution “, International Journal of Production Research, Vol. 55, Issue 21, Pages 6207-6234, 2017.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yazılım Mühendisliği (Diğer)

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

26 Nisan 2024

Yayımlanma Tarihi

30 Nisan 2024

Gönderilme Tarihi

5 Ocak 2024

Kabul Tarihi

4 Nisan 2024

Yayımlandığı Sayı

Yıl 2024 Cilt: 8 Sayı: 1

Kaynak Göster

APA
Elhalid, O. B., & Isık, A. H. (2024). ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION. International Journal of 3D Printing Technologies and Digital Industry, 8(1), 92-103. https://doi.org/10.46519/ij3dptdi.1415512
AMA
1.Elhalid OB, Isık AH. ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION. IJ3DPTDI. 2024;8(1):92-103. doi:10.46519/ij3dptdi.1415512
Chicago
Elhalid, Osama Burak, ve Ali Hakan Isık. 2024. “ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION”. International Journal of 3D Printing Technologies and Digital Industry 8 (1): 92-103. https://doi.org/10.46519/ij3dptdi.1415512.
EndNote
Elhalid OB, Isık AH (01 Nisan 2024) ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION. International Journal of 3D Printing Technologies and Digital Industry 8 1 92–103.
IEEE
[1]O. B. Elhalid ve A. H. Isık, “ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION”, IJ3DPTDI, c. 8, sy 1, ss. 92–103, Nis. 2024, doi: 10.46519/ij3dptdi.1415512.
ISNAD
Elhalid, Osama Burak - Isık, Ali Hakan. “ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION”. International Journal of 3D Printing Technologies and Digital Industry 8/1 (01 Nisan 2024): 92-103. https://doi.org/10.46519/ij3dptdi.1415512.
JAMA
1.Elhalid OB, Isık AH. ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION. IJ3DPTDI. 2024;8:92–103.
MLA
Elhalid, Osama Burak, ve Ali Hakan Isık. “ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION”. International Journal of 3D Printing Technologies and Digital Industry, c. 8, sy 1, Nisan 2024, ss. 92-103, doi:10.46519/ij3dptdi.1415512.
Vancouver
1.Osama Burak Elhalid, Ali Hakan Isık. ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION. IJ3DPTDI. 01 Nisan 2024;8(1):92-103. doi:10.46519/ij3dptdi.1415512

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