Reference number : GC-2017-Q1-02868, amendment number : , agreement type : G, recipient legal name : Pesant, Gilles (École Polytechnique de Montréal), recipient country : CA, recipient province : nan, recipient city : Quebec|Québec, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : 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., program purpose french : 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., agreement title english : Exploiting the Combinatorial Structures Found in Constraint Programming Models as Multivariate Distributions, agreement title french : Exploiting the Combinatorial Structures Found in Constraint Programming Models as Multivariate Distributions, agreement number : RGPIN, agreement value : 210000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada