Local Search Neighbourhoods to Deal with a Novel Nurse Rostering Model

A novel nurse rostering model is developed to represent real world problem instances more accurately. The proposed model is generic in a way that different problem instances can be successfully represented. Novel local search neighbourhoods are developed to take advantage of the problem properties represented by the model. These neighbourhoods are utilised within a variable neighbourhood search algorithm. The performance of the solution method is evaluated empirically on real world data. Experimental results are processed using statistical methods. An adaptive version of the solution method that uses problem instance properties to select the neighbourhood set is also proposed and experimented with. The proposed model is prone to further extensions to cover personnel planning problems in different sectors and countries. Associated new solution methods can be studied to handle these extensions.