Comparison and hybridization of crossover operators for the nurse scheduling problem

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 subject to various hard constraints. In the literature, several gene...

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Bibliographic Details
Published inAnnals of operations research Vol. 159; no. 1; pp. 333 - 353
Main Authors Maenhout, Broos, Vanhoucke, Mario
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.03.2008
Springer Nature B.V
Subjects
Business and Management
Combinatorics
Costs
Genetic algorithms
Heuristic
Hybridization
Nurses
Operations research
Operations Research/Decision Theory
Preferences
Schedules
Scheduling
Studies
Theory of Computation
Nurse scheduling
Hybridization
Meta-heuristics
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Summary: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 subject to various hard constraints. In the literature, several genetic algorithms have been proposed 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.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-007-0268-z