The general employee scheduling problem: an integration of MS and AI
Computers and Operations Research - Special issue: Applications of integer programming
Improved implicit optimal modeling of the labor shift scheduling problem
Management Science
Tabu Search
Classification of Various Neighborhood Operations for the Nurse Scheduling Problem
ISAAC '00 Proceedings of the 11th International Conference on Algorithms and Computation
A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
A Polyhedral Approach for the Staff Rostering Problem
Management Science
The State of the Art of Nurse Rostering
Journal of Scheduling
Finding good nurse duty schedules: a case study
Journal of Scheduling
On the performance of Scatter Search for post-enrolment course timetabling problems
Journal of Combinatorial Optimization
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In this paper, we present a scatter search algorithm for the well-known nurse scheduling problem (NSP). This problem aims at the construction of roster schedules for nurses taking both hard and soft constraints into account. The objective is to minimize the total preference cost of the nurses and the total penalty cost from violations of the soft constraints. The problem is known to be NP-hard. The contribution of this paper is threefold. First, we are, to the best of our knowledge, the first to present a scatter search algorithm for the NSP. Second, we investigate two different types of solution combination methods in the scatter search framework, based on four different cost elements. Last, we present detailed computational experiments on a benchmark dataset presented recently, and solve these problem instances under different assumptions. We show that our procedure performs consistently well under many different circumstances, and hence, can be considered as robust against case-specific constraints.