This paper discusses and analyses the tradeoff between the flexibility afforded with greater number of staff and the implied cost of employing extra staff in the context of the nurse-scheduling problem. If the number of staff is constant, our study allows quantification of the degree of pressure put on the staff resulting from the schedules that do not satisfy their preferences for shift alloca...

[3] Dr.S.Khumaraguru Associate professor Department of Mathematics Chikkanna government Arts College Tirupur Abstract The aim of this paper is to operationalize the concept of nursing schedule quality in such a way that it can cope with the nature of nursing schedule quality. This operationalization describes, the concept of nursing schedule quality needs to be analyzed in such a way that all v...

This paper presents a general optimisation-based rostering engine developed by the University of Auckland. This engine is designed to solve a wide range of personnel scheduling (staff rostering) problems. The engine is currently being used to roster over 700 staff at an Australian call centre and also for the rostering of 50 immigration staff at Auckland International Airport. It is being trial...

We applied simulated annealing algorithm to nurse scheduling problem. For time complexity problem of simulated annealing, we suggested an efficient transition rule using cost matrix for simulated annealing. The experimental results showed that the suggested method generated a nurse scheduling faster in time and better in quality compared to traditional simulated annealing.

Nurse staffing and scheduling is a major health human resource issue currently facing healthcare organizations. To increase the capacity of healthcare organizations to address a variety of issues related to nurse staffing and scheduling, a mult-isite collaborative project was undertaken. The primary focus of this project was

We applied a genetic algorithm to the nurse scheduling problem. To improve performance of the genetic algorithm, we suggested an efficient operator using a cost bit matrix. The experimental results showed that the suggested method generated a nurse scheduling faster in time and better in quality compared to a traditional genetic algorithm.