Nurse scheduling using constraint logic programming
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
A Memetic Approach to the Nurse Rostering Problem
Applied Intelligence
Case-Bases Incorporating Scheduling Constraint Dimensions - Experiences in Nurse Rostering
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Employee Timetabling, Constraint Networks and Knowledge-Based Rules: A Mixed Approach
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
A Tabu-Search Hyperheuristic for Timetabling and Rostering
Journal of Heuristics
An indirect genetic algorithm for a nurse-scheduling problem
Computers and Operations Research
Variable neighborhood search for nurse rostering problems
Metaheuristics
The State of the Art of Nurse Rostering
Journal of Scheduling
Cyclic preference scheduling of nurses using a Lagrangian-based heuristic
Journal of Scheduling
Hybrid optimization techniques for the workshift and rest assignment of nursing personnel
Artificial Intelligence in Medicine
Solving nurse rostering problems using soft global constraints
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
A categorisation of nurse rostering problems
Journal of Scheduling
One hyper-heuristic approach to two timetabling problems in health care
Journal of Heuristics
A harmony search algorithm for nurse rostering problems
Information Sciences: an International Journal
A Time Predefined Variable Depth Search for Nurse Rostering
INFORMS Journal on Computing
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This paper investigates an adaptive constructive method for solving nurse rostering problems. The constraints considered in the problems are categorised into three classes: those that are sequence related, those that are nurse schedule related and those that are roster related. We propose a decomposition approach (to construct solutions) that consists of two stages: (1) to construct high quality sequences for nurses by only considering the sequence constraints, and (2) to iteratively construct schedules for nurses and the overall rosters, based on the sequences built and considering the schedule and roster constraints. In the second stage of the schedule construction, nurses are ordered and selected adaptively according to the quality of the schedules they were assigned to in the last iteration. Greedy local search is carried out during and after the roster construction, in order to improve the (partial) rosters built. We show that the local search heuristic during the roster construction can further improve the constructed solutions for the benchmark problems tested.In addition, we introduce new benchmark nurse rostering datasets which are based upon real world data. The data sets represent a variety of real world constraints. The publication of this problem data to the research community is aimed at closing the gap between theory and practice in nurse scheduling research. One of the main objectives is to encourage more research on these data sets.