An Indirect Genetic Algorithm for a Nurse Scheduling Problem

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

This is the latest version of this item.

[img] PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (249kB)

Abstract

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.

Item Type: Article
Uncontrolled Keywords: Genetic Algorithms, Heuristics, Manpower Scheduling
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 30 Oct 2007 14:48
Last Modified: 30 Oct 2007 14:48
URI: http://eprints.nottingham.ac.uk/id/eprint/661

Available Versions of this Item

  • An Indirect Genetic Algorithm for a Nurse Scheduling Problem. (deposited 30 Oct 2007 14:48) [Currently Displayed]

Actions (Archive Staff Only)

Edit View Edit View