An Indirect Genetic Algorithm for a Nurse Scheduling Problem
This paper describes a Genetic Algorithms approach to a manpower-scheduling problem arising at a major UK hospital. Although Genetic Algorithms have been successfully used for similar problems in the past, they always had to overcome the limitations of the classical Genetic Algorithms paradigm in ha...
| Main Authors: | , |
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| Format: | Article |
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2004
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| Online Access: | https://eprints.nottingham.ac.uk/661/ |
| _version_ | 1848790457429000192 |
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| author | Aickelin, Uwe Dowsland, Kathryn |
| author_facet | Aickelin, Uwe Dowsland, Kathryn |
| author_sort | Aickelin, Uwe |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper describes a Genetic Algorithms approach to a manpower-scheduling problem arising at a major UK hospital. Although Genetic Algorithms have been successfully used for similar problems in the past, they always had to overcome the limitations of the classical Genetic Algorithms paradigm in handling the conflict between objectives and constraints. The approach taken here is to use an indirect coding based on permutations of the nurses, and a heuristic decoder that builds schedules from these permutations. Computational experiments based on 52 weeks of live data are used to evaluate three different decoders with varying levels of intelligence, and four well-known crossover operators. Results are further enhanced by introducing a hybrid crossover operator and by making use of simple bounds to reduce the size of the solution space. The results reveal that the proposed algorithm is able to find high quality solutions and is both faster and more flexible than a recently published Tabu Search approach. |
| first_indexed | 2025-11-14T18:12:55Z |
| format | Article |
| id | nottingham-661 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:12:55Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-6612020-05-04T20:31:17Z https://eprints.nottingham.ac.uk/661/ An Indirect Genetic Algorithm for a Nurse Scheduling Problem Aickelin, Uwe Dowsland, Kathryn This paper describes a Genetic Algorithms approach to a manpower-scheduling problem arising at a major UK hospital. Although Genetic Algorithms have been successfully used for similar problems in the past, they always had to overcome the limitations of the classical Genetic Algorithms paradigm in handling the conflict between objectives and constraints. The approach taken here is to use an indirect coding based on permutations of the nurses, and a heuristic decoder that builds schedules from these permutations. Computational experiments based on 52 weeks of live data are used to evaluate three different decoders with varying levels of intelligence, and four well-known crossover operators. Results are further enhanced by introducing a hybrid crossover operator and by making use of simple bounds to reduce the size of the solution space. The results reveal that the proposed algorithm is able to find high quality solutions and is both faster and more flexible than a recently published Tabu Search approach. 2004 Article PeerReviewed Aickelin, Uwe and Dowsland, Kathryn (2004) An Indirect Genetic Algorithm for a Nurse Scheduling Problem. Computers & Operations Research, 31 (5). pp. 761-778. ISSN 0305-0548 Genetic Algorithms Heuristics Manpower Scheduling http://www.elsevier.com/wps/find/journaldescription.cws_home/300/description#description doi:10.1016/S0305-0548(03)00034-0 doi:10.1016/S0305-0548(03)00034-0 |
| spellingShingle | Genetic Algorithms Heuristics Manpower Scheduling Aickelin, Uwe Dowsland, Kathryn An Indirect Genetic Algorithm for a Nurse Scheduling Problem |
| title | An Indirect Genetic Algorithm for a Nurse Scheduling Problem |
| title_full | An Indirect Genetic Algorithm for a Nurse Scheduling Problem |
| title_fullStr | An Indirect Genetic Algorithm for a Nurse Scheduling Problem |
| title_full_unstemmed | An Indirect Genetic Algorithm for a Nurse Scheduling Problem |
| title_short | An Indirect Genetic Algorithm for a Nurse Scheduling Problem |
| title_sort | indirect genetic algorithm for a nurse scheduling problem |
| topic | Genetic Algorithms Heuristics Manpower Scheduling |
| url | https://eprints.nottingham.ac.uk/661/ https://eprints.nottingham.ac.uk/661/ https://eprints.nottingham.ac.uk/661/ |