Nurse Scheduling Problem (NSP) is the problem that allocating shifts (day and night shifts, holidays, and so on) for nurses under various constraints. Generally, NSP has a lot of constraints. As a result, it needs a lot of knowledge and experience to make the scheduling table with its constraints, and it has been made by the head nurse or the authority in the hospitals. Some researches for NSP using Genetic Algorithm (GA) have been reported. The conventional methods take the constraints into the fitness function. However, if it reduces the fitness value a lot to the parts of solution against the constraints, it causes useless search. Because most of chromosomes are selected in the initial population or as the change by the genetic operations. And if it doesn't reduce the fitness value so much, the final solution has some parts against the constraints. Some of them are established by the Labor Standards Act or the Labor Union Act, so the solution has to be modified. As a result, it is difficult to acquire an effective scheduling table automatically. We study the method of the coding and the genetic operations with their constraints for NSP. In this paper, we propose a new coding method and genetic operations considering the constraints. We apply this method to the NSP using actual shifts and constraints being used in a hospital. It shows that an effective scheduling table satisfying the constraints is acquired by this method.