Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital

محفوظ في:
التفاصيل البيبلوغرافية
الحاوية / القاعدة:Applied Sciences vol. 15, no. 7 (2025), p. 3610
المؤلف الرئيسي: Narlı, Müfide
مؤلفون آخرون: Derse, Onur
منشور في:
MDPI AG
الموضوعات:
الوصول للمادة أونلاين:Citation/Abstract
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الوسوم: إضافة وسم
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024 7 |a 10.3390/app15073610  |2 doi 
035 |a 3188787438 
045 2 |b d20250101  |b d20251231 
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100 1 |a Narlı, Müfide  |u Department of Industrial Engineering, Faculty of Engineering, Çukurova University, Adana 01330, Türkiye; <email>mnarli@cu.edu.tr</email> 
245 1 |a Optimal Crew Scheduling in an Intensive Care Unit: A Case Study in a University Hospital 
260 |b MDPI AG  |c 2025 
513 |a Case Study Journal Article 
520 3 |a Effective crew scheduling in hospitals with multiple personnel groups is essential for time efficiency and fair workload distribution. This study focuses on optimizing shift scheduling for a team of nurses, doctors, and caregivers working in the Pediatric Intensive Care Unit (PICU) of a university hospital. The model is implemented and solved using GAMS 23.5 software to minimize total staffing costs while ensuring balanced shift allocations. The scheduling process in PICUs is influenced by multiple factors, including staff skills, experience levels, personal preferences, contractual agreements, and hospital demands. Since these factors affect doctors, nurses, and caregivers differently, the model considers each personnel group separately while integrating them into a unified optimization framework. The proposed model successfully generates an annual optimal shift schedule for 10 doctors, 14 nurses, and 9 caregivers, ensuring equitable workload distribution and compliance with hospital regulations. By implementing this scheduling approach, employee satisfaction is enhanced, service quality is improved, and administrative workload is reduced. Additionally, the model ensures a well-balanced distribution of responsibilities, minimizes scheduling inefficiencies, and significantly reduces the time required for shift planning. Ultimately, this study provides a fast, fair, and cost-effective solution for hospital workforce management. 
651 4 |a Turkey 
653 |a Mathematical programming 
653 |a Scheduling 
653 |a Software 
653 |a Integer programming 
653 |a Mathematical models 
653 |a Optimization techniques 
653 |a Interdisciplinary aspects 
653 |a Labor shortages 
653 |a Workforce 
653 |a Hospitals 
653 |a Linear programming 
653 |a Algorithms 
653 |a Caregivers 
653 |a Heuristic 
653 |a Workloads 
653 |a Intensive care 
653 |a Pediatrics 
653 |a Nurses 
653 |a Efficiency 
653 |a Physicians 
700 1 |a Derse, Onur  |u Department of Industrial Engineering, Faculty of Engineering, Tarsus University, Mersin 33400, Türkiye 
773 0 |t Applied Sciences  |g vol. 15, no. 7 (2025), p. 3610 
786 0 |d ProQuest  |t Publicly Available Content Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3188787438/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3188787438/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3188787438/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch