Implicit modeling of flexible break assignments in optimal shift scheduling
Management Science
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
A Hybrid Tabu Search Algorithm for the Nurse Rostering Problem
SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning
Staff scheduling at the United States postal service
Computers and Operations Research
Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
Manufacturing & Service Operations Management
The State of the Art of Nurse Rostering
Journal of Scheduling
A 0-1 goal programming model for nurse scheduling
Computers and Operations Research
Implicit shift scheduling with multiple breaks and work stretch duration restrictions
Journal of Scheduling
Monthly tour scheduling models with mixed skills considering weekend off requirements
Computers and Industrial Engineering
Long-term staff scheduling with regular temporal distribution
Computer Methods and Programs in Biomedicine
A categorisation of nurse rostering problems
Journal of Scheduling
Hybrid optimization techniques for the workshift and rest assignment of nursing personnel
Artificial Intelligence in Medicine
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In this work, we propose a general integer programming model to address the staff scheduling problem, flexible enough to be easily adapted to a wide-range of real-world problems. The model is applied with slight changes to two case studies: a glass plant and a continuous care unit, and also to a collection of benchmark instances available in the literature. The emphasis of our approach is on a novel formulation of sequence constraints and also on workload balance, which is tackled through cyclic scheduling. Models are solved using the CPLEX solver. Computational results indicate that optimal solutions can be achieved within a reasonable amount of time.