Title
Applying Simulated Annealing to the Nurse Rostering Problem in an Emergency Department.
Abstract
As living standards rise, patient requirements for medical quality increase. To provide better service, human resource management of hospitals has become a critical issue. Because the shortage of manpower and hospitals must have nursing staff standing by round the clock, unreasonable roster may be generated. As a result, nursing staff do not have enough rest time, resulting in low work efficiency. To prevent this situation, a roster satisfying the requirements of both the nursing staff and the health care regulations is required. This is especially true of the emergency department, discussed in this study. An emergency department may have 12 types of shifts and over one hundred nursing staff to be scheduled. In addition to the hard constraints of legal regulations and hospital policies, staff scheduling should also consider the soft constraints of the personal preferences of individual nursing staff. This makes it a time-consuming work. Therefore, this study proposes a simulated annealing (SA) algorithm to solve this problem. In order to validate performance of the algorithm, data collected from the emergency department of a large-scale hospital in northern Taiwan was scheduled via our approach and compared with the manual rosters. The results showed that the SA obtained a roster which met both the hard and soft constraints, as well as the requirements of the hospital, within one hour, even in months with tight manpower.
Year
DOI
Venue
2014
10.3233/978-1-61499-440-4-852
MOVING INTEGRATED PRODUCT DEVELOPMENT TO SERVICE CLOUDS IN THE GLOBAL ECONOMY
Keywords
Field
DocType
Nurse Rostering Problem,Emergency,Simulated Annealing
Simulated annealing,Emergency medicine,Emergency department,Medical emergency,Medicine
Conference
Volume
ISSN
Citations 
1
2352-7528
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Shih-Wei Lin113.72
Yueh-E. Lee200.34
Li-Chen Chen300.34
Her-Kun Chang400.34
Chih-Feng Lin500.34