Implicit modeling of flexible break assignments in optimal shift scheduling
Management Science
Improved implicit optimal modeling of the labor shift scheduling problem
Management Science
Optimal shift scheduling with multiple break windows
Management Science
Personnel Tour Scheduling When Starting-Time Restrictions Are Present
Management Science
On global warming: Flow-based soft global constraints
Journal of Heuristics
The theory of grammar constraints
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Constraint programming based column generation for employee timetabling
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Grammar-Based Integer Programming Models for Multiactivity Shift Scheduling
Management Science
On matrices, automata, and double counting
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Assigning multiple activities to work shifts
Journal of Scheduling
A hybrid MIP/CP approach for multi-activity shift scheduling
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
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Many optimisation problems contain substructures involving constraints on sequences of decision variables. Such constraints can be very complex to express with mixed integer programming (MIP), while in constraint programming (CP), the global constraint regulareasily represents this kind of substructure with deterministic finite automata (DFA). In this paper, we use DFAs and the associated layered graph structure built for the regularconstraint consistency algorithm to develop a MIP version of the constraint. We present computational results on an employee timetabling problem, showing that this new modeling approach can significantly decrease computational times in comparison with a classical MIP formulation.