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Tracking non-stationary optimal solution by particle swarm optimizer

  • X. Cui
  • , C. T. Hardin
  • , R. K. Ragade
  • , T. E. Potok
  • , A. S. Elmaghraby

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

    19 Scopus citations

    Abstract

    In the real world, we have to frequently deal with searching for and tracking an optimal solution in a dynamic environment. This demands that the algorithm not only find the optimal solution but also track the trajectory of the solution in a dynamic environment. Particle Swarm Optimization (PSO) is a population-based stochastic optimization technique, which can find an optimal, or near optimal, solution to a numerical and qualitative problem. However, the traditional PSO algorithm lacks the ability to track the optimal solution in a dynamic environment. In this paper, we present a modified PSO algorithm that can be used for tracking a non-stationary optimal solution in a dynamically changing environment.

    Original languageEnglish
    Title of host publicationProceedings - Sixth Int. Conf. on Softw. Eng., Artif. Intelligence, Networking and Parallel/Distributed Computing and First ACIS Int. Workshop on Self-Assembling Wireless Networks, SNPD/SAWN 2005
    Pages133-138
    Number of pages6
    DOIs
    StatePublished - 2005
    Event6th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and 1st ACIS International Workshop on Self-Assembling Wireless Networks, SNPD/SAWN 2005 - Towson, MD, United States
    Duration: May 23 2005May 25 2005

    Publication series

    NameProceedings - Sixth Int. Conf. on Softw. Eng., Artificial Intelligence, Netw. and Parallel/Distributed Computing and First ACIS Int. Workshop on Self-Assembling Wireless Netw., SNPD/SAWN 2005
    Volume2005

    Conference

    Conference6th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and 1st ACIS International Workshop on Self-Assembling Wireless Networks, SNPD/SAWN 2005
    Country/TerritoryUnited States
    CityTowson, MD
    Period05/23/0505/25/05

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