Genetic Algorithm Based System for Patient Scheduling in Highly Constrained Situations
CBMS'97 Proceedings of the 10th conference on Computer based medical systems
An Integer Programming-Based Nurse Rostering System
ASIAN '96 Proceedings of the Second Asian Computing Science Conference on Concurrency and Parallelism, Programming, Networking, and Security
Patient scheduling under uncertainty
Proceedings of the 2004 ACM symposium on Applied computing
A hybrid tabu search algorithm for automatically assigning patients to beds
Artificial Intelligence in Medicine
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High demand but limited staffs within some services of a hospital require a proper scheduling of staff and patients. In this study, a hierarchical mathematical model is proposed to generate weekly staff scheduling. Due to computational difficulty of this scheduling problem, the entire model is broken down into manageable three hierarchical stages: (1) selection of patients, (2) assignment of patients to the staff, (3) scheduling of patients throughout a day. The developed models were tested on the data collected in College of Medicine Research Hospital at Cukurova University using GAMS and MPL optimization packages. From the results of the case study, the presented hierarchical model provided a schedule that ensures to maximize the number of selected patients, to balance the workload of physiotherapist, and to minimize waiting time of patients in their treatment day.