Enhanced Greedy Optimization Algorithm with Data Warehousing for Automated Nurse Scheduling System

R. M. Kapila Taranga Ratnayaka, Zhong-Jun Wang, Satish Anamalamudi, Siyue Cheng

College of Engineering, Colorado State University, Fort Collins, USA.
Department of Statistics, Science College, Wuhan University of Technology, Wuhan, China.
School of Information Engineering, Wuhan University of Technology, Wuhan, China.

DOI: 10.4236/etsn.2012.14007                

Abstract

Current Nurse scheduling process has many challenges like work plan creation and working hour allocation for employees at specific planning horizon. Hospitals in most of the developing countries use manual methods to create nurse scheduling systems. With current existing manual nurse scheduling systems, most of the hospitals especially in developing countries don’t have efficient work plan allocation. Moreover, patients need nursing care throughout the day. Hence, current manual nurse scheduling approach with simple statistical functions is not efficient especially for highly populated countries. Our proposed automated nurse scheduling approach has carried out in two stages. Firstly, we propose an efficient data warehouse system based on online analytical method for hospital information system. Subsequently, Enhanced Greedy Optimization algorithm is implemented to optimize the nurse roster and compared with other optimization algorithms (Simulated Annealing and Genetic Algorithm). Experimental results (MYSQL, JAVA, OLAP) with proposed optimization algorithm outperforms compared with existing optimization solutions.

Keywords

Java; MYSQL; Date Warehouse; OLAP

Conflicts of Interest

The authors declare no conflicts of interest.

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