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Nurse Scheduling by Cooperative GA with Effective Virus Operator

Nurse Scheduling by Cooperative GA with Effective Virus Operator

Makoto Ohki
Copyright: © 2014 |Volume: 5 |Issue: 1 |Pages: 11
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781466652392|DOI: 10.4018/ijaec.2014010102
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MLA

Ohki, Makoto. "Nurse Scheduling by Cooperative GA with Effective Virus Operator." IJAEC vol.5, no.1 2014: pp.19-29. http://doi.org/10.4018/ijaec.2014010102

APA

Ohki, M. (2014). Nurse Scheduling by Cooperative GA with Effective Virus Operator. International Journal of Applied Evolutionary Computation (IJAEC), 5(1), 19-29. http://doi.org/10.4018/ijaec.2014010102

Chicago

Ohki, Makoto. "Nurse Scheduling by Cooperative GA with Effective Virus Operator," International Journal of Applied Evolutionary Computation (IJAEC) 5, no.1: 19-29. http://doi.org/10.4018/ijaec.2014010102

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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.

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