Local and Global Search Based PSO Algorithm

  • Yanxia Sun
  • Zenghui Wang
  • Barend Jacobus van Wyk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7928)


In this paper, a new algorithm for particle swarm optimisation (PSO) is proposed. In this algorithm, the particles are divided into two groups. The two groups have different focuses when all the particles are searching the problem space. The first group of particles will search the area around the best experience of their neighbours. The particles in the second group are influenced by the best experience of their neighbors and the individual best experience, which is the same as the standard PSO. Simulation results and comparisons with the standard PSO 2007 demonstrate that the proposed algorithm effectively enhances searching efficiency and improves the quality of searching.


Local search global search particle swarm optimisation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yanxia Sun
    • 1
  • Zenghui Wang
    • 2
  • Barend Jacobus van Wyk
    • 1
  1. 1.Department of Electrical EngineeringTshwane University of TechnologyPretoriaSouth Africa
  2. 2.Department of Electrical and Mining EngineeringUniversity of South AfricaFloridaSouth Africa

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