- Title
- Workload coverage through nonsmooth optimization
- Creator
- Sukhorukova, Nadezda; Ugon, Julien; Yearwood, John
- Date
- 2009
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/60022
- Identifier
- vital:1807
- Identifier
-
https://doi.org/10.1080/10556780802576813
- Identifier
- ISSN:1055-6788
- Abstract
- In this paper, workload coverage is the problem of identifying a pattern of days worked and days off, along with the number of hours worked on each work day. This pattern must satisfy certain work-related constraints and fit best to a predefined workload. In our study, we formulate the problem of workload coverage as an optimization problem. We propose a number of models which take into consideration various staffing constraints. For each of these models, our study aims to find a compromise between an accurate workload coverage and the ability to solve the corresponding optimization problems in a reasonable time. Numerical experiments on each model are carried out and the results are presented. Interestingly, the nonlinear programming approaches are found to be competitive with linear programming ones. © 2009 Taylor & Francis.
- Publisher
- Taylor & Francis
- Relation
- Optimization Methods and Software Vol. 24, no. 2 (2009), p. 285-298
- Rights
- Copyright Taylor & Francis.
- Rights
- This metadata is freely available under a CCO license
- Subject
- Convex programming; Linear programming; Workload planning; Dynamic programming; Linearization; Nonlinear programming; Optimization
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