• DocumentCode
    596629
  • Title

    A novel particle swarm optimization based on bacteria quorum sensing mechanism

  • Author

    Jun Cheng ; Rongjun Li

  • Author_Institution
    Sch. of Bus. Adm., South China Univ. of Technol., Guangzhou, China
  • fYear
    2012
  • fDate
    18-20 Oct. 2012
  • Firstpage
    485
  • Lastpage
    488
  • Abstract
    Based on analysis of bacteria quorum sensing phenomenon in natural ecosystem, the mechanism of quorum sensing is incorporated into the particle swarm optimization (PSO) to propose a novel PSO algorithm called particle swarm optimization based on bacteria quorum sensing mechanism (PSOQS), which is composed of the initial population and the sensing population. In this algorithm, the initial population generated a sensing population as the former iterated a certain number. The particles of two populations exchanged according to fitness value in order to embody the law of “survival of the fittest” in biological evolution. The experimental results of six benchmark functions demonstrate the different quorum sensing frequency of the present algorithm.
  • Keywords
    particle swarm optimisation; bacteria quorum sensing mechanism; biological evolution; initial population; natural ecosystem; particle swarm optimization; sensing population; Algorithm design and analysis; Benchmark testing; Microorganisms; Particle swarm optimization; Sensors; Sociology; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-1743-6
  • Type

    conf

  • DOI
    10.1109/ICACI.2012.6463211
  • Filename
    6463211