A Comparison and Hybridization of Crossover Operators for the Nurse Scheduling Problem

B. Maenhout () and Mario Vanhoucke

Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium from Ghent University, Faculty of Economics and Business Administration

Abstract: In this paper, we present a hybrid genetic algorithm for the well-known nurse scheduling problem (NSP). The NSP involves the construction of roster schedules for nursing staff in order to maximize the quality of the roster schedule and to minimize the violations of the minimal coverage requirements subject to various hard case-specific constraints. In literature, several genetic algorithms have been proposed in literature to solve the NSP under various assumptions. The contribution of this paper is twofold. First, we extensively compare the various crossover operators and test them on a standard dataset in a solitary approach. Second, we propose several options to hybridize the various crossover operators.

Keywords: meta-heuristics; hybridization; nurse scheduling (search for similar items in EconPapers)
Pages: 20 pages
Date: 2006-01
New Economics Papers: this item is included in nep-cmp
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Citations: View citations in EconPapers (4)

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http://wps-feb.ugent.be/Papers/wp_06_366.pdf (application/pdf)

Related works:
Journal Article: Comparison and hybridization of crossover operators for the nurse scheduling problem (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:rug:rugwps:06/366

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