Free Search in Multidimensional Space II

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


    Recent publications suggest that resolving multidimensional tasks where optimisation parameters are hundreds and more faces unusual computational limitation. In the same time optimisation algorithms, which perform well on tasks with low number of dimensions, when are applied to high dimensional tasks require infeasible period of time and computational resources. This article presents a novel investigation on Differential Evolution and Particle Swarm Optimisation with enhanced adaptivity and Free Search applied to 200 dimensional versions of three scalable, global, real-value, numerical tests, which optimal values are dependent on dimensions number and virtually unknown for variety of dimensions. The aim is to: (1) identify computational limitations which numerical methods could face on 200 dimensional tests; (2) identify relations between test complexity and period of time required for tests resolving; (3) discover unknown optimal solutions; (4) identify specific methods’ peculiarities which could support the performance on high dimensional tasks. Experimental results are presented and analysed.
    Original languageEnglish
    Title of host publication Lecture Notes in Computer Science
    EditorsIvan Dimov, Stefka Fidanova, Ivan Lirkov
    PublisherSpringer International Publishing AG
    Number of pages8
    ISBN (Electronic)978-3-319-15585-2
    ISBN (Print)978-3-319-15584-5
    Publication statusPublished - 4 Feb 2015
    EventNumerical Methods & Applications: International Conference on Numerical Methods and Applications - Borovets, Bulgaria
    Duration: 20 Aug 201424 Aug 2014

    Publication series

    NameLecture Notes in Computer Science
    ISSN (Print)0302-9743


    ConferenceNumerical Methods & Applications
    Abbreviated titleNMA

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