Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic |
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Authors: | Margarida Vaz Pato Margarida Moz |
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Institution: | (1) Faculty of Economics and Business Administration, Ghent University, Gent, Belgium;(2) Operations &; Technology Management Centre, Vlerick Leuven Gent Management School, Gent, Belgium |
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Abstract: | Nurse rerostering arises when at least one nurse announces that she will be unable to undertake the tasks previously assigned
to her. The problem amounts to building a new roster that satisfies the hard constraints already met by the current one and,
as much as possible, fulfils two groups of soft constraints which define the two objectives to be attained. A bi-objective
genetic heuristic was designed on the basis of a population of individuals characterised by pairs of chromosomes, whose fitness
complies with the Pareto ranking of the respective decoded solution. It includes an elitist policy, as well as a new utopic
strategy, introduced for purposes of diversification. The computational experiments produced promising results for the practical
application of this approach to real life instances arising from a public hospital in Lisbon. |
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Keywords: | Nurse scheduling Rerostering Bi-objective heuristics Genetic algorithms |
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