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This paper introduces DEVIATION, a soft global constraint to obtain balanced solutions. A violation measure of the perfect balance can be defined as the Lp norm of the vector variables minus their mean. SPREAD constraints the sum of square deviations to the mean [5, 7] i.e. the L2 norm. The L1 norm is considered here. Neither criterion subsumes the other… (More)

This paper considers the daily assignment of newborn infant patients to nurses in a hospital. The objective is to balance the workload of the nurses, while satisfying a variety of side constraints. Prior work proposed a MIP model for this problem, which unfortunately did not scale to large instances and only approximated the objective function, since… (More)

SDN simplifies network management by relying on declarativity (high-level interface) and expressiveness (network flexibility). We propose a solution to support those features while preserving high robustness and scalability as needed in carrier-grade networks. Our solution is based on (i) a two-layer architecture separating connectivity and optimization… (More)

Large neighborhood search (LNS) [25] is a framework that combines the expressiveness of constraint programming with the efficiency of local search to solve combinatorial optimization problems. This paper introduces an extension of LNS, called multi-objective LNS (MO-LNS), to solve multi-objective combi-natorial optimization problems ubiquitous in practice.… (More)

The Steel Mill Slab Problem is an optimization benchmark that has been studied for a long time in the constraint-programming community but was only solved efficiently in the two last years. Gargani and Refalo solved the problem using Large Neighborhood Search and Van Henten-ryck and Michel made use of constraint programming with an improved symmetry… (More)

Deviation is a recent constraint to balance a set of variables with respect to a given mean. We show that the propagators recently introduced are not bound-consistent when the mean is rational. We introduce bound-consistent propagators running in linear time with respect to the number of variables. We evaluate the improvement in terms of efficiency and… (More)

- Vianney Le Clément De Saint-Marcq, Pierre Schaus, Christine Solnon, Christophe Lecoutre
- 2013

This paper discusses the usage of sparse sets for integer domain implementation over traditional representations. A first benefit of sparse sets is that they are very cheap to trail and restore. A second key advantage introduced in this work is that sparse sets permit to get delta changes with a very limited cost, allowing efficient incremental propagation.… (More)

Flow reasoning has been successfully used in CP for more than a decade. It was originally introduced by Régin in the well-known Alldifferent and Global Cardinality Constraint (GCC) available in most of the CP solvers. The BinPacking constraint was introduced by Shaw and mainly uses an independent knapsack reasoning in each bin to filter the possible bins… (More)

Assembly line balancing problems (ALBP) are of capital importance for the industry since the first assembly line for the Ford T by Henry Ford. Their objective is to optimize the design of production lines while satisfying the various constraints. Precedence constraints among the tasks are always present in ALBP. The objective is then to place the tasks… (More)