Nurse Scheduling by Cooperative GA with Effective Virus Operator

Makoto Ohki
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Makoto Ohki: Tottori University, Department of Electrical and Electronic Engineering, Tottori, Japan

International Journal of Applied Evolutionary Computation (IJAEC), 2014, vol. 5, issue 1, 19-29

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. 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.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jaec00:v:5:y:2014:i:1:p:19-29

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