An indirect genetic algorithm for a nurse-scheduling problem
Citations
897 citations
Cites background or methods or result from "An indirect genetic algorithm for a..."
...Both the problem and the model are comparable to those presented by Aickelin and Dowsland (2000) and Dowsland (1998) (discussed in Section 3.5). However, Blau and Sear take over- and understaffing into account whereas Aickelin and Dowsland consider solutions with coverage deficiencies as infeasible. The contributions in Aickelin and Dowsland (2000) and Dowsland (1998) are also concerned with achieving optimality. Blau (1985), tries to equalise the distribution of unpopular work in addition to the frequency with which employees are granted requests for shifts or days....
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...Both the problem and the model are comparable to those presented by Aickelin and Dowsland (2000) and Dowsland (1998) (discussed in Section 3....
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...Both the problem and the model are comparable to those presented by Aickelin and Dowsland (2000) and Dowsland (1998) (discussed in Section 3.5). However, Blau and Sear take over- and understaffing into account whereas Aickelin and Dowsland consider solutions with coverage deficiencies as infeasible. The contributions in Aickelin and Dowsland (2000) and Dowsland (1998) are also concerned with achieving optimality. Blau (1985), tries to equalise the distribution of unpopular work in addition to the frequency with which employees are granted requests for shifts or days. This is one of the earlier attempts (besides Warner’s (Warner, 1976)) to evenly treat personnel with respect to workload and preferences. In later contributions (see also Table 18 in Appendix B), the distribution of work among people is often arranged via additional constraints. Anzai and Miura (1987), present a cyclic descent algorithm for a ward in which the personnel members are identical (with respect to skills and work regulations). Anzai and Miura state that their model is too simplified for practical applications. Kostreva and Jennings (1991), solve the nurse scheduling problem in two phases. Groups of feasible schedules are calculated in a first step. The groups respect the minimum staffing requirements and each individual schedule fulfils all major working constraints. In the second phase, the best possible ‘aversion score’, which is based on the preferences of the individual nurses (Kostreva and Genevier, 1989), is calculated. The tackled problems are not complex. All the skill categories are scheduled independently, which comes down to a decomposition into partial problems. Modern nurse rostering practice is not usually compatible with this type of approach. Schaerf and Meisels (1999), present a general definition of employee timetabling problems....
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...Both the problem and the model are comparable to those presented by Aickelin and Dowsland (2000) and Dowsland (1998) (discussed in Section 3.5). However, Blau and Sear take over- and understaffing into account whereas Aickelin and Dowsland consider solutions with coverage deficiencies as infeasible. The contributions in Aickelin and Dowsland (2000) and Dowsland (1998) are also concerned with achieving optimality. Blau (1985), tries to equalise the distribution of unpopular work in addition to the frequency with which employees are granted requests for shifts or days. This is one of the earlier attempts (besides Warner’s (Warner, 1976)) to evenly treat personnel with respect to workload and preferences. In later contributions (see also Table 18 in Appendix B), the distribution of work among people is often arranged via additional constraints. Anzai and Miura (1987), present a cyclic descent algorithm for a ward in which the personnel members are identical (with respect to skills and work regulations). Anzai and Miura state that their model is too simplified for practical applications. Kostreva and Jennings (1991), solve the nurse scheduling problem in two phases....
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...Both the problem and the model are comparable to those presented by Aickelin and Dowsland (2000) and Dowsland (1998) (discussed in Section 3.5). However, Blau and Sear take over- and understaffing into account whereas Aickelin and Dowsland consider solutions with coverage deficiencies as infeasible. The contributions in Aickelin and Dowsland (2000) and Dowsland (1998) are also concerned with achieving optimality....
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706 citations
498 citations
339 citations
Cites methods from "An indirect genetic algorithm for a..."
...Other metaheuristic approaches can be found as follows: Evolutionary Algorithms in Aickelin et al. (2007), Aickelin and Dowsland (2004) and Aickelin and Dowsland (2000); Tabu Search in Bester et al. (2007), Ikegami and Niwa (2003), Dowsland and Thompson (2000) and Dowsland (1998); Scatter Search in…...
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207 citations
Cites background from "An indirect genetic algorithm for a..."
...), only a few incorporate decisions about the composition of shifts in their model [1, 2, 3, 7, 10, 11, 12, 24, 27, 28, 33, 48, 72, 75, 103, 104, 108]....
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...Quality [15, 93, 108, 109] Task restrictions [1, 2, 3, 4, 7, 9, 10, 11, 12, 16, 17, 19, 20, 21, 23, 24, 26, 28, 31, 32, 33, 35, 36, 38, 40, 42, 48, 49, 51, 52, 54, 55, 56, 57, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 77, 80, 81, 83, 84, 85, 88, 89, 91, 92, 94, 97, 99, 100, 102, 103, 104, 105, 107, 111, 114, 115, 121]...
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...89, 91, 94, 100, 102, 105, 111] Nurse grade [1, 2, 3, 9, 10, 11, 16, 17, 21, 24, 26, 31, 32, 38, 65, 68, 70, 88, 92, 104] User definable/undefined [12, 15, 19, 20, 22, 23, 33, 49, 55, 67, 68, 69, 72, 75, 77, 80, 81, 84, 85, 97, 99, 101, 115] Other [21, 54, 66, 93, 110, 121]...
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...Services General [42, 51, 64, 66, 67, 75, 77, 87, 102, 105, 111] Health care [1, 2, 3, 9, 10, 11, 16, 17, 21, 24, 26, 27, 28, 31, 32, 38, 40, 55, 65, 68, 70, 88, 89, 92, 104] Maintenance [37, 56, 71]...
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...Simulated annealing [9, 73, 104, 108, 117] Tabu search [21, 24, 31, 49, 73] Genetic algorithm [1, 2, 3, 9, 33, 57, 99, 111] Greedy algorithm [26, 38, 49] Other [7, 15, 16, 17, 23, 28, 32, 35, 37, 40, 52, 55, 56, 65, 67, 68, 69, 74, 75, 81, 84, 88, 91, 104, 110,...
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References
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"An indirect genetic algorithm for a..." refers background in this paper
...The demand for nurses is fulfilled for every grade on every day and night: skRxaq ks iFj n i ijjkis , )( 1 ∀≥∑ ∑ ∈ = (2) Constraint set (1) ensures that every nurse works exactly one shift pattern from his/her feasible set, and constraint set (2) ensures that the demand for nurses is covered for…...
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32,573 citations
"An indirect genetic algorithm for a..." refers background in this paper
...The rostering problem tackled in this paper can be described as follows....
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12,457 citations
"An indirect genetic algorithm for a..." refers background in this paper
...and mutation operators as explained for instance in Goldberg [ 20 ]....
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6,758 citations