Examinando por Autor "Vega, E."

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  • 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 using a shuffled frog leaping algorithm
    (Springer Verlag, 2016) Soto, R.; Crawford, B.; Vega, E.; Johnson, F.; Paredes, F.
    The manufacturing Cell Design Problem (MCDP) is a well-known problem for lines of manufacture where the main goal is to minimize the inter-cell moves. To solve the MCDP we employ the Shuffled Frog Leaping Algorithm (SFLA), which is a metaheuristic inspired on the natural memetic features of frogs. The frog tries to leap all over the search space for a better result until the stopping criteria is met. The obtained results are compared with previous approaches of the algorithm to test the real efficiency of our proposed SFLA. The results show that the proposed algorithm produces optimal solutions for all the 50 studied instances. © Springer International Publishing Switzerland 2016.
  • Miniatura
    ÍtemAcceso Abierto
    Solving manufacturing cell design problems using an artificial fish swarm algorithm
    (Springer Verlag, 2015) Soto, R.; Crawford, B.; Vega, E.; Paredes, F.
    The design of manufacturing cells is a manufacturing strategy that involves the creation of an optimal design of production plants, whose main objective is to minimize movements and exchange of material between these cells. Optimal solution of large scale manufacturing cell design problems (MCDPs) are often computationally unfeasible and only heuristic and approximate methods are able to handle such problems. Artificial fish swarm algorithm (AFSA) belongs to the swarm intelligence algorithms, which based on population search, are able to solve complex optimization problems. In this paper we present an AFSA-based approach to solve the MCDP by using the classic Boctor’s mathematical model. The obtained results show that the proposed algorithm produces optimal solutions for all the 50 studied instances. © Springer International Publishing Switzerland 2015.