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Browsing by Subject "particle swarm optimization"

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    Item type:Article, Access status: Open Access ,
    Algorytmy stadne w optymalizacji problemów przydziału przy kwadratowym wskaźniku jakości (QAP)
    (Wydawnictwa AGH, 2011) Filipowicz, Bogusław; Kwiecień, Joanna
    This paper presents three swarm algorithms: ant algorithms, particle swarm optimization and bee algorithms, used for solution of quadratic assignment problem, which is a NP-hard optimization problem. The results of experiments performed for selected test problems of quadratic assignment problems from QAPLIB library have been also presented.
  • thumbnail.journal.alt
    Item type:Thesis, Access status: Restricted ,
    Implementacja metody roju cząstek w OpenCL
    (Data obrony: 2014-12-11) Iwaniak, Michał
    Wydział Geologii, Geofizyki i Ochrony Środowiska
    Presented thesis describes Particle Swarm Optimization algorithm, a type of a heuristic algorithm used for many optimization problems. The objective of this paper was to implement PSO utilizing computing power of graphics processing units (GPU) emphasizing research of the impact of selected configuration parameters. Cross-platform availability was the main reason why OpenCL was chosen as the framework in which the algorithm was implemented. Main bottlenecks of GPU parallel implementation were high global memory access time and high execution time of random number generator functions. The former was eliminated by removal of the critical section from the algorithm, while the latter by implementing own RNG algorithm, that executed directly on the kernel.
  • thumbnail.journal.alt
    Item type:Article, Access status: Open Access ,
    Zastosowanie przykładowego algorytmu stadnego w optymalizacji kombinatorycznej
    (Wydawnictwa AGH, 2010) Filipowicz, Bogusław; Kwiecień, Joanna
    Nature-inspired metaheuristic algorithms are successfully applied to combinatorial optimization problems. They incorporate particle swarm optimization inspired by the behaviors of bird flocks. This paper presents the applying of binary particle swarm optimization to the multidimensional knapsack problem. The results of computational experiments for standard test problems have been also presented.