A hybrid constraint integer programming approach to solve nurse scheduling problems
Rahimian, Erfan and Akartunali, Kerem and Levine, John; Hanzálek, Zdenek and Kendall, Graham and McCollum, Barry and Šůcha, Premysl, eds. (2015) A hybrid constraint integer programming approach to solve nurse scheduling problems. In: Mista 2015 Proceedings of the 7th Multidisciplinary International Scheduling Conference. Proceedings of the Multidisciplinary International Conference on Scheduling: Theory and Applications . MISTA, CZE, pp. 429-442. ISBN 978-0954582104 (http://schedulingconference.org/proceedings/2015/m...)
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Abstract
The Nurse Scheduling Problem can be simply defined as assigning a series of shift sequences (schedules) to several nurses over a planning horizon according to some constraints and preferences. The inherent benefits of having higher-quality and more flexible schedules are a reduction in outsourcing costs and an increase of job satisfaction in health organizations. In this paper, we present a novel systematic hybrid algorithm, which combines Integer Programming (IP) and Constraint Programming (CP) to efficiently solve highly-constrained Nurse Scheduling Problems. Our focus is to exploit the problem-specific information to improve the performance of the algorithm, and therefore obtain high-quality solutions as well as strong lower bounds. We test our algorithm based on some real-world benchmark instances. Very competitive results are reported compared to the state-of-the-art algorithms from the recent literature, showing that the proposed algorithm is able to solve a wide variety of real-world instances with different complex structures.
ORCID iDs
Rahimian, Erfan ORCID: https://orcid.org/0000-0003-0532-0700, Akartunali, Kerem ORCID: https://orcid.org/0000-0003-0169-3833 and Levine, John ORCID: https://orcid.org/0000-0001-7016-2978; Hanzálek, Zdenek, Kendall, Graham, McCollum, Barry and Šůcha, Premysl-
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Item type: Book Section ID code: 60156 Dates: DateEvent25 August 2015PublishedSubjects: Science > Mathematics > Computer software Department: Strathclyde Business School > Management Science
Faculty of Science > Computer and Information SciencesDepositing user: Pure Administrator Date deposited: 13 Mar 2017 14:12 Last modified: 11 Nov 2024 15:03 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/60156