Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem
The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including customers and workers preferences while minimising bot...
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| Format: | Conference or Workshop Item |
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Scitepress
2017
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| Online Access: | https://eprints.nottingham.ac.uk/41539/ |
| _version_ | 1848796298231152640 |
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| author | Algethami, Haneen Landa-Silva, Dario Martinez-Gavara, Anna |
| author_facet | Algethami, Haneen Landa-Silva, Dario Martinez-Gavara, Anna |
| author_sort | Algethami, Haneen |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including customers and workers preferences while minimising both operational costs and travelling distance. This study seeks to determine effective combinations of genetic operators combined with heuristics that help to find good solutions for this constrained combinatorial optimisation problem. In particular, it aims to identify the best set of operators that help to maximise customers and workers preferences satisfaction. This paper advances the understanding of how to effectively employ different operators within two variants of genetic algorithms to tackle WSRPs. To tackle infeasibility, an initialisation heuristic is used to generate a conflict-free initial plan and a repair heuristic is used to ensure the satisfaction of constraints. Experiments are conducted using three sets of real-world Home Health Care (HHC) planning problem instances. |
| first_indexed | 2025-11-14T19:45:45Z |
| format | Conference or Workshop Item |
| id | nottingham-41539 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:45:45Z |
| publishDate | 2017 |
| publisher | Scitepress |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-415392020-05-04T18:33:43Z https://eprints.nottingham.ac.uk/41539/ Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem Algethami, Haneen Landa-Silva, Dario Martinez-Gavara, Anna The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including customers and workers preferences while minimising both operational costs and travelling distance. This study seeks to determine effective combinations of genetic operators combined with heuristics that help to find good solutions for this constrained combinatorial optimisation problem. In particular, it aims to identify the best set of operators that help to maximise customers and workers preferences satisfaction. This paper advances the understanding of how to effectively employ different operators within two variants of genetic algorithms to tackle WSRPs. To tackle infeasibility, an initialisation heuristic is used to generate a conflict-free initial plan and a repair heuristic is used to ensure the satisfaction of constraints. Experiments are conducted using three sets of real-world Home Health Care (HHC) planning problem instances. Scitepress 2017-02-23 Conference or Workshop Item PeerReviewed Algethami, Haneen, Landa-Silva, Dario and Martinez-Gavara, Anna (2017) Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem. In: 6th International Conference on Operations Research and Enterprise Systems (ICORES 2017), 23-25 February 2017, Porto, Portugal. Genetic operators Constraints Satisfaction Scheduling and Routing Problem Home Health Care http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0006203304160423 |
| spellingShingle | Genetic operators Constraints Satisfaction Scheduling and Routing Problem Home Health Care Algethami, Haneen Landa-Silva, Dario Martinez-Gavara, Anna Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem |
| title | Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem |
| title_full | Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem |
| title_fullStr | Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem |
| title_full_unstemmed | Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem |
| title_short | Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem |
| title_sort | selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem |
| topic | Genetic operators Constraints Satisfaction Scheduling and Routing Problem Home Health Care |
| url | https://eprints.nottingham.ac.uk/41539/ https://eprints.nottingham.ac.uk/41539/ |