Implicit modeling of flexible break assignments in optimal shift scheduling
Management Science
Artificial Intelligence - Special issue on knowledge representation
Optimal shift scheduling with multiple break windows
Management Science
EasyLocal++: an object-oriented framework for the flexible design of local-search algorithms
Software—Practice & Experience
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Principles of Constraint Programming
Principles of Constraint Programming
Implicit shift scheduling with multiple breaks and work stretch duration restrictions
Journal of Scheduling
An AI-Based Break-Scheduling System for Supervisory Personnel
IEEE Intelligent Systems
A large neighbourhood search approach to the multi-activity shift scheduling problem
Journal of Heuristics
An improved memetic algorithm for break scheduling
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
An improved memetic algorithm for break scheduling
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
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The problem of designing workforce shifts and break patterns is a relevant employee scheduling problem that arises in many contexts, especially in service industries. The issue is to find a minimum number of shifts, the number of workers assigned to them, and a suitable number of breaks so that the deviation from predetermined workforce requirements is minimized. We tackle this problem by means of a hybrid strategy in the spirit of Large Neighborhood Search, which exploits a set of Local Search operators that resort to a Constraint Programming model for assigning breaks. We test this strategy on a set of random and real life instances employed in the literature.