Examinando por Autor "Almonacid, B."
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Ítem Acceso Abierto A migrating birds optimization algorithm for machine-part cell formation problems(Springer Verlag, 2015) Soto, R.; Crawford, B.; Almonacid, B.; Paredes, F.Machine-Part Cell Formation Problems consists in organizing a plant as a set of cells, each one of them processing machines containing the same type of parts. In recent years, different meta-heuristic have been used to solve this problem. This paper addresses the problem of Machine-Part Cell Formation by using the Migrating Birds Optimization algorithm. The computational experiments show that in most of the benchmark problems the results obtained from the proposed approach are better than those obtained by other methods which are reported in the literature. © Springer International Publishing Switzerland 2015.Ítem Acceso Abierto Efficient Parallel Sorting for Migrating Birds Optimization When Solving Machine-Part Cell Formation Problems(Hindawi Publishing Corporation, 2016) Soto, R.; Crawford, B.; Almonacid, B.; Paredes F.The Machine-Part Cell Formation Problem (MPCFP) is a NP-Hard optimization problem that consists in grouping machines and parts in a set of cells, so that each cell can operate independently and the intercell movements are minimized. This problem has largely been tackled in the literature by using different techniques ranging from classic methods such as linear programming to more modern nature-inspired metaheuristics. In this paper, we present an efficient parallel version of the Migrating Birds Optimization metaheuristic for solving the MPCFP. Migrating Birds Optimization is a population metaheuristic based on the V-Flight formation of the migrating birds, which is proven to be an effective formation in energy saving. This approach is enhanced by the smart incorporation of parallel procedures that notably improve performance of the several sorting processes performed by the metaheuristic. We perform computational experiments on 1080 benchmarks resulting from the combination of 90 well-known MPCFP instances with 12 sorting configurations with and without threads. We illustrate promising results where the proposal is able to reach the global optimum in all instances, while the solving time with respect to a nonparallel approach is notably reduced. © 2016 Ricardo Soto et al.Ítem Acceso Abierto Un eficiente intercambio de líder en el algoritmo Optimización de Migración de Aves en resolver el problema de formación de celdas máquina-parte [Efficient leader exchange for Migrating Birds Optimization when solving machine-part cell formation problems](IEEE Computer Society, 2016) Soto, R.; Crawford, B.; Almonacid, B.The machine-part cell formation (MPCF) problem is to organize an assembly as a set of cells, where each cell contains certain machines that process a sub-set of parts. In recent years, different types of metaheuristics have been used to solve the problem of MPCF. This publication focuses on solving the MPCF problem using a metaheuristic inspired on birds, called Migrating Birds Optimization (MBO) algorithm. Experiments have been conducted to 180 test instances using 2 types of leader exchange in the flock of birds. The results obtained using MBO are equal to or better than other algorithms reported in the literature. © 2016 AISTI.Ítem Acceso Abierto Machine-part cell formation problems with constraint programming(IEEE Computer Society, 2016) Soto, R.; Crawford, B.; Almonacid, B.; Paredes, F.; Loyola, E.Machine-Part Cell Formation consists on organizing a plant as a set of cells, each one of them processing machines containing different part types. In recent years, different techniques have been used to solve this problem ranging from exact to approximate methods. This paper focuses on solving new instances of this problem for which no optimal value exists by using the classic Boctor's mathematical model. We employ constraint programming as the underlying solving technique illustrating that global optimums are achieved for the whole set of tested instances. © 2015 IEEE.Ítem Acceso Abierto Optimization for UI design via metaheuristics(Springer Verlag, 2016) Soto, R.; Crawford, B.; Almonacid, B.; Niklander, S.; Olguín, E.In recent years, different optimization problems have been arose in the context of UI design. Initially those problems were solved by hand with no computational optimization support since the set of potential design combinations was limited. However, when the space of different possible designs increase, the use of optimization algorithms is mandatory. However, several UI design problems are quadratic, for which guaranteeing the global optimum is not possible in polynomial time. Then the use of classic exact methods may not be feasible. In this paper, we briefly present how metaheuristics can straightforwardly be used to model and solve interesting but complex quadratic problems from UI design. In particular, we employ Cuckoo Search, which is a modern optimization technique to solve a well-known problem concerned to keyboard layout optimization. © Springer International Publishing Switzerland 2016.Ítem Acceso Abierto Resolución del manufacturing cell design problem utilizando el algoritmo Bat [A Bat algorithm to solve the manufacturing cell design problem](IEEE Computer Society, 2016) Soto, R.; Crawford, B.; Zec, C.; Alarcon A.; Almonacid, B.Manufacturing Cell Design is a problem that is aimed at distributing the different machines of a center of production in cells, so that the parts of the final product to be manufactured with the least amount of travel in its manufacturing process. Bat Algorithm is an algorithm inspired by the behavior of echolocation in bats. Using a balance sheet of the frequency and automatic tuning of exploration and exploitation by controlling the rate of volume and emission pulses. The following work shows the resolution of the Manufacturing Cell Design, by means of Bat Algorithm, an algorithm that proved to be effective for this problem because it has reached the optimum in all problems with which the tests were conducted. © 2016 AISTI.Ítem Acceso Abierto Resolución del manufacturing cell design problem utilizando el algoritmo Luciérnaga [A firefly algorithm to solve the manufacturing cell design problem](IEEE Computer Society, 2016) Soto, R.; Crawford, B.; Lama, J.; Almonacid, B.This research focuses on modeling and solving the Manufacturing Cell Design Problem (MCDP) through a Firefly Algorithm (FA). The MCDP consists in creating an optimal design of production plants, through the creation of cells that group machines and parts. The goal of the problem is to minimize movements and exchange of material between the cells. The FA is a metaheuristic based on the mating behavior or flash of fireflies, in order to communicate with each other or attract potential prey. Fireflies move through the search space by means of attraction that they feel toward other fireflies until the stop criteria established is complied. Finally, to test the efficiency of FA, the results obtained have been compared with previous research illustrating encouraging results. © 2016 AISTI.Ítem Acceso 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.