A parameter free algorithm of cooperative genetic algorithm for nurse scheduling problem

This paper describes a technique of penalty weight adjustment for the Cooperative Genetic Algorithm applied to the nurse scheduling problem. In this algorithm, coefficient and thresholds for each penalty function are automatically optimized. Therefore, this technique provides a parameter free algorithm of nurse scheduling. The nurse scheduling is very complex task, because many requirements must be considered. These requirements are implemented by a set of penalty function in this research. In real hospital, several changes of the schedule often happen. Such changes of the shift schedule yields various inconveniences, for example, imbalance of the number of the holidays and the number of the attendance. Such inconvenience causes the fall of the nursing level of the nurse organization. Reoptimization of the schedule including the changes is very hard task and requires very long computing time. We consider that this problem is caused by the solution space having many local minima. We propose a technique to adjust penalty weights and thresholds through the optimization to escape from the local minima.