Authors:
Makoto Ohki
and
Hideaki Kinjo
Affiliation:
Graduate School of Tottori University, Japan
Keyword(s):
Nurse scheduling, Genecit algorithm, Cooperative genecitic algorithm, Penalty coefficient adjustment.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Society and Cultural Aspects of Evolution
;
Soft Computing
Abstract:
This paper describes a penalty adjustment technique for CGA applied to the nurse scheduling problem. The
nurse scheduling is very complex task, because many requirements must be considered. In real hospital, some
changes of the schedule often happen. Such a change of the shift schedule yields various inconveniences.
Such an inconvenience causes the fall of the nursing level of the whole nurse organization. Furthermore,
reoptimization of the schedule including such changes is very hard task and requires very long computing
time. To improve this problem, we propose a technique to adjust penalty coefficient through the optimization.