Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
383375 | Expert Systems with Applications | 2013 | 10 Pages |
•An agent-based cooperative framework is applied to fairness in nurse rostering.•Computational experiments show cooperation produces the fairest nurse rosters.•This is one of the first studies using cooperation for fairness in nurse rostering.
The development of decision support systems acceptable for nurse rostering practitioners still presents a daunting challenge. Building on an existing nurse rostering problem, a set of fairness-based objective functions recently introduced in the literature has been extended. To this end, a generic agent-based cooperative search framework utilising new mechanisms is described, aiming to combine the strengths of multiple metaheuristics. These different metaheuristics represent individual planners’ implicit procedures for improving rosters. The framework enables to explore different ways of assessing nurse rosters in terms of fairness objectives. Computational experiments have been conducted across a set of benchmark instances. The overall results indicate that the proposed cooperative search for fair nurse rosters outperforms each metaheuristic run individually.