원문정보
보안공학연구지원센터(IJSEIA)
International Journal of Software Engineering and Its Applications
Vol.8 No.1
2014.01
pp.53-62
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
We applied genetic algorithm to nurse scheduling problem. For time complexity problem of genetic algorithm, we suggested efficient operators using a cost bit matrix of which each cell indicates any violation of constraints. A cell with 1 indicates that the corresponding assignment violates constraints and needs no further consideration. The experimental results showed that the suggested method generated a nurse scheduling faster in time and better in quality compared to the traditional genetic algorithm.
목차
Abstract
1. Introduction
2. Problem Description
2.1. Nurse Scheduling Problem
2.2. Cost Function
3. Algorithmic Flow of CMGA
3.1. Genetic Algorithms
3.2. Selection and Crossover for CMGA
3.3. A Cost Bit Matrix and Mutation for CMGA
4. Experiments and Results
5. Conclusion and Future Work
Acknowledgements
References
1. Introduction
2. Problem Description
2.1. Nurse Scheduling Problem
2.2. Cost Function
3. Algorithmic Flow of CMGA
3.1. Genetic Algorithms
3.2. Selection and Crossover for CMGA
3.3. A Cost Bit Matrix and Mutation for CMGA
4. Experiments and Results
5. Conclusion and Future Work
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보