Multi-population inflationary differential evolution algorithm with adaptive local restart

Di Carlo, Marilena and Vasile, Massimiliano and Minisci, Edmondo; (2015) Multi-population inflationary differential evolution algorithm with adaptive local restart. In: 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., JPN, pp. 632-639. ISBN 9781479974924

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    Abstract

    In this paper a Multi-Population Inflationary Differential Evolution algorithm with Adaptive Local Restart is presented and extensively tested over more than fifty test functions from the CEC 2005, CEC 2011 and CEC 2014 competitions. The algorithm combines a multi-population adaptive Differential Evolution with local search and local and global restart procedures. The proposed algorithm implements a simple but effective mechanism to avoid multiple detections of the same local minima. The novel mechanism allows the algorithm to decide whether to start or not a local search. The local restart of the population, which follows the local search, is, therefore, automatically adapted.

    Creators(s): Di Carlo, Marilena ORCID logoORCID: https://orcid.org/0000-0001-5046-3028, Vasile, Massimiliano ORCID logoORCID: https://orcid.org/0000-0001-8302-6465 and Minisci, Edmondo ORCID logoORCID: https://orcid.org/0000-0001-9951-8528;
    Item type:Book Section
    ID code:53402
    Keywords:global optimization , differential evolution, multi-population algorithm, adaptive algorithm, Mechanical engineering and machinery, Motor vehicles. Aeronautics. Astronautics, Mechanical Engineering, Aerospace Engineering, Control and Systems Engineering
    Subjects:Technology > Mechanical engineering and machinery
    Technology > Motor vehicles. Aeronautics. Astronautics
    Department:Faculty of Engineering > Mechanical and Aerospace Engineering
    Technology and Innovation Centre > Advanced Engineering and Manufacturing
    Depositing user: Pure Administrator
    Date deposited:16 Jun 2015 15:58
    Last modified:29 May 2020 01:11
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/53402
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