Nurse Scheduling by Cooperative GA with Effective Virus Operator

Nurse Scheduling by Cooperative GA with Effective Virus Operator

Makoto Ohki (Tottori University, Department of Electrical and Electronic Engineering, Tottori, Japan)
Copyright: © 2014 |Pages: 11
DOI: 10.4018/ijaec.2014010102
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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. The authors propose a virus operator for the cooperative GA, which does not lose consistency of the nurse schedule. The cooperative GA with the new operator has brought a surprisingly good result, it has never been brought by the conventional algorithm.
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General hospitals consist of several sections such as the internal medicine department and the pediatrics department, etc. About fifty to thirty nursing staffs belong in each section. A section manager constitutes a roster, or a shift schedule, of all nurses of her/his section every month. In our interviewing research to several real hospitals, we found that the manager considers more than fifteen requirements for the scheduling. Such the schedule arrangement, in other words, the nurse scheduling, is a very complex task. We call such the problem Nurse Scheduling Problem (NSP). In the interview, even a veteran manager has to spend one or two weeks to complete the nurse scheduling. This means a great loss of work force. Therefore, computer software for solving NSP has recently come to be required in the general hospitals (Goto, 1993; Berrada, 1996; Takaba, 1998; Ikegami, 2001; Burke, 2001a; Kawanaka, 2002; Inoue, 2002; Itoga, 2003; Cheang, 2003; Burke, 2004a; Ernst, 2004; Burke, 2004b; Li, 2004; Bard, 2005; Oezcan, 2005; Burke, 2006; Bard, 2007).

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