Nurse rostering is a complex scheduling problem that affects hospitalpersonnel on a daily basis all over the world. This paper presents a newcomponent-based approach with adaptive perturbations, for a nurse schedulingproblem arising at a major UK hospital. The main idea behind this technique isto decompose a schedule into its components (i.e. the allocated shift patternof each nurse), and then mimic a natural evolutionary process on thesecomponents to iteratively deliver better schedules. The worthiness of allcomponents in the schedule has to be continuously demonstrated in order forthem to remain there. This demonstration employs a dynamic evaluation functionwhich evaluates how well each component contributes towards the finalobjective. Two perturbation steps are then applied: the first perturbationeliminates a number of components that are deemed not worthy to stay in thecurrent schedule; the second perturbation may also throw out, with a low levelof probability, some worthy components. The eliminated components arereplenished with new ones using a set of constructive heuristics using localoptimality criteria. Computational results using 52 data instances demonstratethe applicability of the proposed approach in solving real-world problems.
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