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
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;
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
DOI :
10.1109/ICACI.2012.6463211