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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/7127

    Título
    Integrated Design of a Supermarket Refrigeration System by Means of Experimental Design Adapted to Computational Problems
    Autor
    Sarabia Ortiz, DanielAutoridad UBU Orcid
    Ortiz Fernández, Mª CruzAutoridad UBU Orcid
    Sarabia Peinador, Luis AntonioAutoridad UBU Orcid
    Publicado en
    Algorithms. 2022, V. 15, n. 11: 417
    Editorial
    MDPI
    Fecha de publicación
    2022-11
    ISSN
    1999-4893
    DOI
    10.3390/a15110417
    Abstract
    In this paper, an integrated design of a supermarket refrigeration system has been used to obtain a process with better operability. It is formulated as a multi-objective optimization problem where control performance is evaluated by six indices and the design variables are the number and discrete power of each compressor to be installed. The functional dependence between design and performance is unknown, and therefore the optimal configuration must be obtained through a computational experimentation. This work has a double objective: to adapt the surface response methodology (SRM) to optimize problems without experimental variability as are the computational ones and show the advantage of considering the integrated design. In the SRM framework, the problem is stated as a mixture design with constraints and a synergistic cubic model where a D-optimal design is applied to perform the experiments. Finally, the multi-objective problem is reduced to a single objective one by means of a desirability function. The optimal configuration of the power distribution of the three compressors, in percentage, is (50,20,20). This solution has an excellent behaviour with respect to the six indices proposed, with a significant reduction in time oscillations of controlled variables and power consumption compared with other possible power distributions.
    Palabras clave
    Computational experiment
    D-optimal
    Integrated design and control
    Surrogate model
    Desirability
    Experimental design
    Hybrid Model Predictive Control
    Mixture
    Materia
    Matemáticas
    Mathematics
    Ingeniería
    Engineering
    Informática
    Computer science
    URI
    http://hdl.handle.net/10259/7127
    Versión del editor
    https://doi.org/10.3390/a15110417
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