Competitive Nurse Rostering and Rerostering
Abstract
Nurse rostering is the assignment of specific nurses to specific shifts for a future scheduling period. The work schedule that is created is called a roster. The reconstruction of a disrupted roster is called rerostering. When solving the rostering and rerostering problems there are two considerations: the organization's costs and the nurses preferences. Traditional solution methods, often based on integer programs (IP), have two short comings; first, they rely on one objective function to represent both the organization's and nurses goals; second, rostering requires either the complete resolving of the rostering problem or a new solution method to fix the roster. We propose three agent-based auction heuristics, Competitive Nurse Rostering (CNR), an extension called CNR-Iterated Local Search (CNR-ILS), and an extension of CNR-ILS called CNRRerostering (CNRR). These heuristics are the first nurse rostering methods that model each nurse's preferences in separate objective functions. The heuristics are the first competitive agent-based rostering and rerostering methods. They uniquely separate the organizational cost and nurse preference problems by constraining the preference problem s solutions space to alternate cost optimal solutions. CNRR is the first rostering solution that can reroster nurses. When tested in a real hospital, CNR and CNR-ILS solved the rostering problem 99% faster than the hospital s rostering method and an IP solution from the literature. Nurses consistently favored the solutions from CNR-ILS compared to those from CNR, the IP and the hospital. CNRR finds solutions to the rerostering problem over 90% of the time. Less than one sixth of the solutions had a serious impact to nurse preferences.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2008
- Accession Number
- ADA476319
Entities
People
- Michael V. Chiaramonte
Organizations
- Arizona State University