Decomposition techniques with mixed integer programming and heuristics for home healthcare planning
- Submitting institution
-
University of Nottingham, The
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1318850
- Type
- D - Journal article
- DOI
-
10.1007/s10479-016-2352-8
- Title of journal
- Annals of Operations Research
- Article number
- -
- First page
- 93
- Volume
- 256
- Issue
- 1
- ISSN
- 0254-5330
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 7
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Social care needs are increasing at a higher pace than are the resources available to provide it, making effective, efficient scheduling of nurses and carers essential. This paper’s identification of an optimisation methodology producing high-quality schedules for the large problems seen in real-world scenarios is significant in allowing practical application. The work also brought new problem instances to the literature and underpins an impact case studies returned by the UOA. Parts of the methodology have been incorporated into OptifAI, the world-class intelligence scheduler around which the new company NDGAI was created (https://www.ndgai.com/optifai/#optifai). Contact: Rodrigo Pinheiro, Data Science Director (rodrigo.pinheiro@ndgai.com).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
