Parallel Imperialist Competitive Algorithms

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

    Research output: Contribution to journalArticleScientificpeer-review

    10 Citations (Scopus)


    The importance of optimization and NP-problem solving cannot be overemphasized. The usefulness

    and popularity of evolutionary computing methods are also well established. There are

    various types of evolutionary methods; they are mostly sequential but some of them have parallel

    implementations as well.We propose a multi-population method to parallelize the Imperialist

    CompetitiveAlgorithm. The algorithm has been implementedwith the Message Passing Interface

    on 2 computer platforms, and we have tested our method based on shared memory and message

    passing architectural models. An outstanding performance is obtained, demonstrating that

    the proposed method is very efficient concerning both speed and accuracy. In addition, compared

    with a set of existingwell-known parallel algorithms, our approach obtainsmore accurate results

    within a shorter time period.

    Original languageUndefined/Unknown
    Pages (from-to)
    JournalConcurrency and Computation: Practice and Experience
    Issue number7
    Publication statusPublished - 2018
    MoE publication typeA1 Journal article-refereed

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