SUPER-SAPSO: A New SA-Based PSO Algorithm

Majid Bahrepour, Elham Mahdipour, Raman Cheloi, Mahdi Yaghoobi

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    5 Citations (Scopus)
    92 Downloads (Pure)

    Abstract

    Swarm Optimisation (PSO) has been received increasing attention due to its simplicity and reasonable convergence speed surpassing genetic algorithm in some circumstances. In order to improve convergence speed or to augment the exploration area within the solution space to find a better optimum point, many modifications have been proposed. One of such modifications is to fuse PSO with other search strategies such as Simulated Annealing (SA) in order to make a new hybrid algorithm – so called SAPSO. To the best of the authors’ knowledge, in the earlier studies in terms of SAPSO, the researchers either assigned an inertia factor or a global temperature to particles decreasing in the each iteration globally. In this study the authors proposed a local temperature, to be assigned to the each particle, and execute SAPSO with locally allocated temperature. The proposed model is called SUPERSAPSO because it often surpasses the previous SAPSO model and standard PSO appropriately. Simulation results on different benchmark functions demonstrate superiority of the proposed model in terms of convergence speed as well as optimisation accuracy.
    Original languageEnglish
    Title of host publicationApplications of Soft Computing
    Subtitle of host publicationFrom Theory to Praxis
    EditorsJörn Mehnen, Mario Köppen, Ashraf Saad, Ashutosh Tiwari
    Place of PublicationBerlin
    PublisherSpringer
    Pages423-430
    Number of pages8
    ISBN (Electronic)978-3-540-89619-7
    ISBN (Print)978-3-540-89618-0
    DOIs
    Publication statusPublished - 2 Nov 2008
    Event13th World Conference on Soft Computing in Industrial Applications, WSC 2008 -
    Duration: 10 Nov 200828 Nov 2008
    Conference number: 13

    Publication series

    NameAdvances in Itelligent and Soft Computing
    PublisherSpringer
    Volume58
    ISSN (Print)1867-5662
    ISSN (Electronic)1867-5670

    Conference

    Conference13th World Conference on Soft Computing in Industrial Applications, WSC 2008
    Abbreviated titleWSC
    Period10/11/0828/11/08

    Keywords

    • METIS-263991
    • IR-67863
    • Genetic Algorithm
    • CR-I.2
    • PSO
    • EWI-15997
    • Particle Swarm Optimization

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