An improved multimodal PSO method based on electrostatic interaction using n- nearest-neighbor local search

نویسندگان

  • Taymaz Rahkar-Farshi
  • Sara Behjat-Jamal
  • Mohammad-Reza Feizi-Derakhshi
چکیده

In this paper, an improved multimodal optimization (MMO) algorithm,calledLSEPSO,has been proposed. LSEPSO combinedElectrostatic Particle Swarm Optimization (EPSO) algorithm and a local search method and then madesome modification onthem. It has been shown to improve global and local optima finding ability of the algorithm. This algorithm useda modified local search to improve particle's personal best, which usedn-nearest-neighbour instead of nearest-neighbour. Then, by creating n new points among each particle and n nearest particles, it triedto find a point which could be the alternative of particle's personal best. This methodprevented particle's attenuation and following a specific particle by its neighbours. The performed tests on a number of benchmark functions clearly demonstratedthat the improved algorithm is able to solve MMO problems and outperform other tested algorithms in this article.

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عنوان ژورنال:
  • CoRR

دوره abs/1410.2056  شماره 

صفحات  -

تاریخ انتشار 2014