A domain transformation approach for addressing staff scheduling problems
Staff scheduling is a complex combinatorial optimisation problem concerning allocation of staff to duty rosters in a wide range of industries and settings. This thesis presents a novel approach to solving staff scheduling problems, and in particular nurse scheduling, by simplifying the problem space...
| Main Author: | |
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
| Published: |
2016
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| Online Access: | https://eprints.nottingham.ac.uk/31249/ |
| _version_ | 1848794159600631808 |
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| author | Baskaran, Geetha |
| author_facet | Baskaran, Geetha |
| author_sort | Baskaran, Geetha |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Staff scheduling is a complex combinatorial optimisation problem concerning allocation of staff to duty rosters in a wide range of industries and settings. This thesis presents a novel approach to solving staff scheduling problems, and in particular nurse scheduling, by simplifying the problem space through information granulation. The complexity of the problem is due to a large solution space and the many constraints that need to be satisfied. Published research indicates that methods based on random searches of the solution space did not produce good-quality results consistently. In this study, we have avoided random searching and proposed a systematic hierarchical method of granulation of the problem domain through pre-processing of constraints. The approach is general and can be applied to a wide range of staff scheduling problems.
The novel approach proposed here involves a simplification of the original problem by a judicious grouping of shift types and a grouping of individual shifts into weekly sequences. The schedule construction is done systematically, while assuring its feasibility and minimising the cost of the solution in the reduced problem space of weekly sequences. Subsequently, the schedules from the reduced problem space are translated into the original problem space by taking into account the constraints that could not be represented in the reduced space. This two-stage approach to solving the scheduling problem is referred to here as a domain-transformation approach.
The thesis reports computational results on both standard benchmark problems and a specific scheduling problem from Kajang Hospital in Malaysia. The results confirm that the proposed method delivers high-quality results consistently and is computationally efficient. |
| first_indexed | 2025-11-14T19:11:46Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-31249 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:11:46Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-312492025-02-28T11:46:06Z https://eprints.nottingham.ac.uk/31249/ A domain transformation approach for addressing staff scheduling problems Baskaran, Geetha Staff scheduling is a complex combinatorial optimisation problem concerning allocation of staff to duty rosters in a wide range of industries and settings. This thesis presents a novel approach to solving staff scheduling problems, and in particular nurse scheduling, by simplifying the problem space through information granulation. The complexity of the problem is due to a large solution space and the many constraints that need to be satisfied. Published research indicates that methods based on random searches of the solution space did not produce good-quality results consistently. In this study, we have avoided random searching and proposed a systematic hierarchical method of granulation of the problem domain through pre-processing of constraints. The approach is general and can be applied to a wide range of staff scheduling problems. The novel approach proposed here involves a simplification of the original problem by a judicious grouping of shift types and a grouping of individual shifts into weekly sequences. The schedule construction is done systematically, while assuring its feasibility and minimising the cost of the solution in the reduced problem space of weekly sequences. Subsequently, the schedules from the reduced problem space are translated into the original problem space by taking into account the constraints that could not be represented in the reduced space. This two-stage approach to solving the scheduling problem is referred to here as a domain-transformation approach. The thesis reports computational results on both standard benchmark problems and a specific scheduling problem from Kajang Hospital in Malaysia. The results confirm that the proposed method delivers high-quality results consistently and is computationally efficient. 2016-02-20 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/31249/1/Geetha%20Baskaran%20PhD%20Thesis.pdf Baskaran, Geetha (2016) A domain transformation approach for addressing staff scheduling problems. PhD thesis, University of Nottingham. scheduling domain transformation information granulation |
| spellingShingle | scheduling domain transformation information granulation Baskaran, Geetha A domain transformation approach for addressing staff scheduling problems |
| title | A domain transformation approach for addressing staff scheduling problems |
| title_full | A domain transformation approach for addressing staff scheduling problems |
| title_fullStr | A domain transformation approach for addressing staff scheduling problems |
| title_full_unstemmed | A domain transformation approach for addressing staff scheduling problems |
| title_short | A domain transformation approach for addressing staff scheduling problems |
| title_sort | domain transformation approach for addressing staff scheduling problems |
| topic | scheduling domain transformation information granulation |
| url | https://eprints.nottingham.ac.uk/31249/ |