Subventions et des contributions :

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Titre :

Exploiting the Combinatorial Structures Found in Constraint Programming Models as Multivariate Distributions

Numéro de l’entente :

RGPIN

Valeur d'entente :

210 000,00 $

Date d'entente :

10 mai 2017 -

Organisation :

Conseil de recherches en sciences naturelles et en génie du Canada

Location :

Québec, Autre, CA

Numéro de référence :

GC-2017-Q1-02868

Type d'entente :

subvention

Type de rapport :

Subventions et des contributions

Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023)

Nom légal du bénéficiaire :

Pesant, Gilles (École Polytechnique de Montréal)

Programme :

Programme de subventions à la découverte - individuelles

But du programme :

Many sectors of the economy rely on our ability to solve complex combinatorial problems in order to plan, organize, or schedule their activities in the best way possible. For example: scheduling nurses in a hospital according to their individual skills and preferences so that they cover the forecast demand in patient care, and assigning patients to them so as to achieve a balanced workload; or planning the construction of a forest road network in order to harvest and then transport the lumber, designing truck routes between harvesting sites and mills, and building synchronized schedules for trucks and loaders. Among the computerized methods to accomplish this, Constraint Programming represents the problem using a formalism that exposes much of its structure. This research proposes to use that structure in a deeper way in order to improve our ability to solve combinatorial problems. Any progress towards that general goal can apply to each of these sectors and therefore can have a significant impact on our productivity and well being.