Examinando por Autor "Riquelme, L."

Mostrando 1 - 3 de 3
  • Miniatura
    ÍtemAcceso Abierto
    Algoritmo de Optimización basado en biogeografía para resolver el Set Covering Problem [Biogeography-based Optimization Algorithm for the Set Covering Problem]
    (IEEE Computer Society, 2016) Crawford, B.; Soto, R.; Riquelme, L.; Olguin, E.
    Biogeography-Based Optimization Algorithm (BBOA) is a new kind of global optimization algorithm inspired by biogeography, which mimics the migration behavior of animals in nature to solve optimization and engineering problems. In this paper, we proposed BBOA for solving the Set Covering Problem (SCP). The SCP is a classic combinatorial problem from NP-hard list problems, consisting in find a set of solutions that cover a range of needs at the lowest possible cost with certain constraints. Moreover, we proposed a new feature for improve performance of BBOA, improving stagnation in local optimum. Finally, the experiments with BBOA to solve these problems, show very good results. © 2016 AISTI.
  • Miniatura
    ÍtemAcceso Abierto
    Biogeography-based optimization algorithm for solving the set covering problem
    (Springer Verlag, 2016) Crawford, B.; Soto, R.; Riquelme, L.; Olguín, E.
    Biogeography-Based Optimization Algorithm (BBOA) is a kind of new global optimization algorithm inspired by biogeography. It mimics the migration behavior of animals in nature to solve optimization and engineering problems. In this paper, BBOA for the Set Covering Problem (SCP) is proposed. SCP is a classic combinatorial problem from NP-hard list problems. It consist to find a set of solutions that cover a range of needs at the lowest possible cost following certain constraints. In addition, we provide a new feature for improve performance of BBOA, improving stagnation in local optimum. With this, the experiment results show that BBOA is very good at solving such problems. © Springer International Publishing Switzerland 2016.
  • Miniatura
    ÍtemAcceso Abierto
    Set covering problem resolution by Biogeography-Based Optimization Algorithm
    (Springer Verlag, 2016) Crawford, B.; Soto, R.; Riquelme, L.; Olguín, E.; Misra, S.
    The research on Artificial Intelligence and Operational Research has provided models and techniques to solve many industrial problems. For instance, many real life problems can be formulated as a Set Covering Problem (SCP). The SCP is a classic NP-hard combinatorial problem consisting in find a set of solutions that cover a range of needs at the lowest possible cost following certain constraints. In this work, we use a recent metaheuristic called Biogeography-Based Optimization Algorithm (BBOA) inspired by biogeography, which mimics the migration behavior of animals in nature to solve optimization and engineering problems. In this paper, BBOA for the SCP is proposed. In addition, to improve performance we provide a new feature for the BBOA, which improve stagnation in local optimum. Finally, the experiment results show that BBOA is a excellent method for solving such problems. © Springer International Publishing Switzerland 2016.