Precision in High Dimensional Optimisation of Global Tasks with Unknown Solutions

    Research output: Chapter in Book/Report/Published conference proceedingChapterpeer-review


    High dimensional optimisation is a challenge for most of the available search methods. Resolving global and constrained task seems to be even harder and exploration of tasks with unknown solutions can be seen very rare in the literature and requires more research efforts. This article analyses optimisation of high dimensional global, including constrained, tasks with unknown solutions. Reviewed and analysed are experimental results precision, possibilities for trapping in local sub-optima and adaptation to unknown search spaces.
    Original languageEnglish
    Title of host publicationLarge-Scale Scientific Computing
    Subtitle of host publicationLSSC 2019. Lecture Notes in Computer Science
    EditorsIvan Lirkov, Svetozar Margenov
    Place of PublicationCham
    PublisherSpringer Nature
    Number of pages6
    ISBN (Electronic)978-3-030-41032-2
    ISBN (Print)978-3-030-41031-5
    Publication statusPublished - 13 Jan 2020

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11958 LNCS

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