ENHANCING MEDICAL OFFICER SCHEDULING IN HEALTHCARE ORGANIZATIONS: A COMPREHENSIVE INVESTIGATION OF GENETIC AND GOOGLE OR TOOLS ALGORITHMS FOR MULTI-PROJECT RESOURCE-CONSTRAINED OPTIMIZATION
Öz
Anahtar Kelimeler
Kaynakça
- 1. Google Corporation, “Google Developers”, http://developers.google.com/, January 9, 2024.
- 2. GeeksforGeeks, “Genetic Algorithms”, https://www.geeksforgeeks.org/genetic-algorithms/. January 9, 2024.
- 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. 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. 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. Mahmud, F., “Evolutionary Algorithms for Resource Constrained Project Scheduling Problems “, Doctoral Thesis, UNSW University, Sydney, 2023.
- 7. El-Abbasy, M. S. K., “Multi-objective multi-project construction scheduling optimization“, Doctoral Thesis, Concordia University, Montreal, 2015.
- 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
Yazarlar
Ali Hakan Isık
0000-0003-3561-9375
Türkiye
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
Cited By
OPTIMIZING CONVOLUTIONAL NEURAL NETWORKS WITH SIMULATED ANNEALING FOR HEART DISEASE PREDICTION
Mühendislik Bilimleri ve Tasarım Dergisi
https://doi.org/10.21923/jesd.1638469