Scalable Computation of High-Order Optimization Queries.

Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do...

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Publicado en:Communications of the ACM Vol. 62; no. 2; pp. 108 - 117
Autores principales: Brucato, Matteo, Abouzied, Azza, Meliou, Alexandra
Formato: Artículo
Publicado: Association for Computing Machinery Feb2019
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2019
      vid: 62
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        atl: Scalable Computation of High-Order Optimization Queries.
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        au:
          Brucato, Matteo
          Abouzied, Azza
          Meliou, Alexandra
        affil:
          College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA.
          Computer Science, New York University, Abu Dhabi, UAE.
      su:
        Querying (Computer science)
        Constrained optimization
        Query languages (Computer science)
        Computer programming
        Database searching
      sug:
        subj:
          Querying (Computer science)
          Constrained optimization
          Query languages (Computer science)
          Computer programming
          Database searching
      ab: Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. Our goal is to create a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. We present a complete system that supports package queries, a new query model that extends traditional database queries to handle complex constraints and preferences over answer sets, allowing the declarative specification and efficient evaluation of a significant class of constrained optimization problems—integer linear programs (ILP)—within a database.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
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