Artificial bee colony algorithm for nurse scheduling problem using high-performance computing

The Nurse Rostering Problem (NRP) is a combinatorial optimization problem that is tackled by assigning a set of nurses with different skills and contracts to different types of shifts, over a predefined scheduling period. An efficient nurse scheduling process allows hospitals to better handle last-minute changes and stay in compliance with labor laws. It also ensures smooth and effective communication among employees, and between schedulers and employees. The nurse rostering problem is characterized by the presence of a large set of constraints, which are usually divided into two categories: hard and soft constraints. Hard constraints are those that are rigidly enforced and should be met at all times. Violations of the soft constraints are to be avoided, if possible. Bee Colony Optimization (BCO) algorithm is proposed to tackle the NRP tested on a dataset of 30 nurses introduced in the First International Nurse Rostering Competition (INRC2010). The algorithm iteratively searches for the solution by going through a validation process which involves filtering the solution through all the constraints. The results produced by the proposed algorithm are very promising when compared with those produced by the five INRC2010 winners’ methods. Further investigation is still necessary for further improvement of the proposed algorithm.

• Hovedforfatter: Aristizábal Scacco, Daniel Santiago (author)
• Format: bachelorThesis
• Sprog: eng
• Udgivet: 2023
• Fag: Nurse rostering problem; Swarm intelligence method; Nature-inspired algorithm
• Online adgang: http://repositorio.yachaytech.edu.ec/handle/123456789/635