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Logic-based methods for optimization: combining optimization and constraint satisfaction

A pioneering look at the fundamental role of logic in optimization and constraint satisfaction<br /> <br /> While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to...

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Detalles Bibliográficos
Autor principal: Hooker, John
Lenguaje:eng
Publicado: Wiley 2011
Materias:
Acceso en línea:http://cds.cern.ch/record/2116682
Descripción
Sumario:A pioneering look at the fundamental role of logic in optimization and constraint satisfaction<br /> <br /> While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible