.. Nrps, 1.1 Nurse Rostering Problems, p.160

. Dans-le-cas-de-la-r, egle (P3), si uneinfirmì ere est amenéè a travailler six jours consécutivement alors la violation engendrée sera de, 2000.

R. `-egles-de-séquence-les-contraintes-de-la-famille-de-regular, ou encore ?-Regular) sontparticulì erement bien adaptéesadaptéesà la modélisation de r` egles de séquence. En Chapitre 8. Applications des contraintes globales relaxées aux NRPs entrée un planning satisfaisant seulement un sous-ensemble de contraintes (comme par exemple, les contraintes sur les capacités deséquipesdeséquipes) Une autre possibilité est d'utiliser un solveur tiers ou une recherche arborescente,compì ete ou non, afin de calculer unepremì ere solution

. Dans, différentes heuristiques basées sur l'´ echange (?? swap ??) de larges parties de plannings dinfirmì eres ontétéontété proposées : ? Shuffle neighborhood qui considère des ?? swaps ?? entre les portions du planning de l'in-firmì ere cumulant le plus de violations avec le planning d'une autreinfirmì ere

. Récemment, trois nouvelles heuristiques de choix voisinages ontétéontété proposées dans [HQ09] pour une recherche de type LNS (Large Neighborhood Search, p.17

G. Azaiez, AS05] Grâcè a l'utilisation de la programmation par but, une solution optimale est trouvée en 600 secondes sur un Pentium 700 MHz

L. Réseau, AllDifferent(µ dec ) pourraitêtre pourraitêtre réutilisé en pondérant les arcs de violation pour modéliser les préférencespréférencesémises Afin de pondérer demanì ere fine les arcs de violation, certaines informations structurelles peuventêtrepeuventêtre utilisées. Par exemple, les arcs de violation issus d'une valeur ne doiventêtredoiventêtre pondérés que par les poids associés aux contraintes dont les variables possèdent cette valeur dans leur domaine. Il est aussi possible d'utiliser les variables dont le domaine est réduitréduità un singleton pour affiner le poids de certains arcs. Un second avantage d'une telle représentation permettrait de s'abstraire de l

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