Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. The need for quality software solutions is acute for a number of reasons. In particular, it is very important to efficiently utilise time and effort, to evenly balance the workload among people and to attempt to satisfy personnel preferences. A high quality roster can lead to a more contented and thus more effective workforce.In this review, we discuss nurse rostering within the global personnel scheduling problem in healthcare. We begin by briefly discussing the review and overview papers that have appeared in the literature and by noting the role that nurse rostering plays within the wider context of longer term hospital personnel planning. The main body of the paper describes and critically evaluates solution approaches which span the interdisciplinary spectrum from operations research techniques to artificial intelligence methods. We conclude by drawing on the strengths and weaknesses of the literature to outline the key issues that need addressing in future nurse rostering research.

In the Team Orienteering Problem with Time Windows (TOPTW) a set of locations is given, each with a score, a service time and a time window. The goal is to determine a fixed number of routes, limited in length, that visit, at the right time, some locations and maximise the sum of the collected scores. This paper describes a simple, fast and effective iterated local search meta-heuristic to solve the TOPTW. An insert step is combined with a shake step to escape local optima.The specific shake step implementation produces a heuristic that performs very well on a large set of instances with up to 288 locations. The obtained results have an average gap with the optimal solution of only 1.8% for instances with only a single route and 2.1% for instances with three to twenty routes.

Abstract. This paper deals with the problem of nurse rostering in Belgian hospitals. This is a highly constrained real world problem that was (until the results of this research were applied) tackled manually. The problem basically concerns the assignment of duties to a set of people with different qualifications, work regulations and preferences. Constraint programming and linear programming techniques can produce feasible solutions for this problem. However, the reality in Belgian hospitals forced us to use heuristics to deal with the over constrained schedules. An important reason for this decision is the calculation time, which the users prefer to reduce. The algorithms presented in this paper are a commercial nurse rostering product developed for the Belgian hospital market, entitled Plane.

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