Adaptive neighborhood search for nurse rostering

This paper presents an adaptive neighborhood search method (ANS) for solving the nurse rostering problem proposed for the First International Nurse Rostering Competition (INRC-2010). ANS uses jointly two distinct neighborhood moves and adaptively switches among three intensification and diversification search strategies according to the search history. Computational results assessed on the three sets of 60 competition instances show that ANS improves the best known results for 12 instances while matching the best bounds for 39 other instances. An analysis of some key elements of ANS sheds light on the understanding of the behavior of the proposed algorithm.

► ANS is an adaptive neighborhood search method for nurse rostering.
► ANS switches among 3 search (intensive, intermediate, diversification) strategies.
► ANS uses jointly two move operators in a probabilistic way.
► ANS improves and mactches respectively 12 and 39 best known INRC-2011 bounds.