A novel population-based local search for nurse rostering problem

Population-based approaches regularly are better than single based (local search) in exploring the search space. However, drawback of population-based is exploiting Several hybrid have proven their efficiency through different domains optimization problems by incorporating and integrating strength population local approaches. Meanwhile, methods a increasing parameter tuning. Recently, was proposed for university course-timetabling problem with fewer parameters existing approaches, approach proves its effectiveness. The employs two operators to intensify diversify first operator applied solution, while second all solutions. This paper aims investigate performance nurse rostering problem. INRC2010 database dataset composed 69 instances used test PB-LS. A comparison made between PB-LS other literature. Results show good performances compared where provided best results 55 cases over experiments.