Examinando por Autor "Reyes, V."

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  • Miniatura
    ÍtemAcceso Abierto
    A beam-search approach to the set covering problem
    (Springer Verlag, 2016) Reyes, V.; Araya, I.; Crawford, B.; Soto, R.; Olguín, E.
    In this work we present a beam-search approach applied to the Set Covering Problem. The goal of this problem is to choose a subset of columns of minimal cost covering every row. Beam Search constructs a search tree by using a breadthfirst search strategy, however only a fixed number of nodes are kept and the rest are discarded. Even though original beam search has a deterministic nature, our proposal has some elements that makes it stochastic. This approach has been tested with a well-known set of 45 SCP benchmark instances from OR-Library showing promising results. © Springer International Publishing Switzerland 2016.
  • Miniatura
    ÍtemAcceso Abierto
    Solving manufacturing cell design problems by using a bat algorithm approach
    (Springer Verlag, 2016) Soto, R.; Crawford, B.; Alarcón, A.; Zec, C.; Vega, E.; Reyes, V.; Araya, I.; Olguín, E.
    Manufacturing Cell Design is a problem that consist in distributing machines in cells, in such a way productivity is improved. The idea is that a product, build up by using different parts, has the least amount of travel on its manufacturing process. To solve the MCDP we use the Bat Algorithm, a metaheuristic inspired by a feature of the microbats, the echolocation. This feature allows an automatic exploration and exploitation balance, by controlling the rate of volume and emission pulses during the search. Our approach has been tested by using a well-known set of benchmark instances, reaching optimal values for most of them. © Springer International Publishing Switzerland 2016.
  • Miniatura
    ÍtemAcceso Abierto
    Solving manufacturing cell design problems by using a dolphin echolocation algorithm
    (Springer Verlag, 2016) Soto, R.; Crawford, B.; Carrasco, C.; Almonacid, B.; Reyes, V.; Araya, I.; Misra, S.; Olguín, E.
    The Manufacturing Cell Design is a problem that consist in organize machines in cells to increase productivity, i.e., minimize the movement of parts for a given product between machines. In order to solve this problem we use a Dolphin Echolocation algorithm, a recent bio-inspired metaheuristic based on a dolphin feature, the echolocation. This feature is used by the dolphin to search all around the search space for a target, then the dolphin exploits the surround area in order to find promising solutions. Our approach has been tested by using a set of 10 benchmark instances with several configurations, reaching to optimal values for all of them. © Springer International Publishing Switzerland 2016.