Authors:
Makoto Ohki
;
Shin-ya Uneme
;
Shigeto Hayashi
and
Masaaki Ohkita
Affiliation:
Faculty of Engineering, Tottori University, Japan
Keyword(s):
Genetic Algorithm, Cooperative GA, Mutation Operator, Virus Operator, Nurse Scheduling, Scheduling Problem.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Planning and Scheduling
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
This paper proposes effective genetic operators for cooperative genetic algorithm (GA) to solve a nurse scheduling problem. A clinical director of a medical department makes a duty schedule of all nurses of the department every month. Such the scheduling is very complex task. It takes one or two weeks to create the nurse schedule even by a veteran director. In conventional ways using the cooperative GA, a crossover operator is only employed for the optimization, because it does not lose consistency between chromosomes. We propose a mutation operator and a virus operator for the cooperative GA, which does not lose consistency of the nurse schedule. The cooperative GA with these new operators has brought a surprisingly good result, it has never been brought by the conventional algorithm.