PICA: Multi-Population Implementation of Parallel Imperialist Competitive Algorithms

Amin Majd, Shahriar Lotfi, Golnaz Sahebi, Masoud Daneshtalab, Juha Plosila

    Forskningsoutput: Kapitel i bok/konferenshandlingKonferensbidragVetenskapligPeer review

    9 Citeringar (Scopus)

    Sammanfattning

    The importance of optimization and NP-problems solving cannot be over emphasized. The usefulness and popularity of evolutionary computing methods are also well established. There are various types of evolutionary methods that are mostly sequential, and some others have parallel implementation. We propose a method to parallelize Imperialist Competitive Algorithm (Multi-Population). The algorithm has been implemented with MPI on two platforms and have tested our algorithms on a shared-memory and message passing architecture. An outstanding performance is obtained, which indicates that the method is efficient concern to speed and accuracy. In the second step, the proposed algorithm is compared with a set of existing well known parallel algorithms and is indicated that it obtains more accurate solutions in a lower time.

    OriginalspråkOdefinierat/okänt
    Titel på gästpublikation2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)
    FörlagIEEE
    Sidor
    DOI
    StatusPublicerad - 2016
    MoE-publikationstypA4 Artikel i en konferenspublikation
    EvenemangEuromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP) - 2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)
    Varaktighet: 17 feb 201619 feb 2019

    Konferens

    KonferensEuromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)
    Period17/02/1619/02/19

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