DocumentCode :
1602901
Title :
A Multi-swarm Based Hybird Optimization Algorithm in Dynamic Environments
Author :
Yu, Yan
Author_Institution :
Inst. of Comput. Sci. & Inf. Eng., Harbin Normal Univ., Harbin, China
Volume :
4
fYear :
2010
Firstpage :
63
Lastpage :
66
Abstract :
This paper analyzes the effect of population size to PSO algorithm and proposes Dynamic particle population based particle swarm optimization (DPP-PSO),the core idea of which is that, according to the search, particle swarm dynamically change particle population and gradually decrease the particles with lower search ability when population size are converging constantly and gradually increase new particles to expand the global search ability. The collaborative optimization of these items decrease calculated amount and improve globe exploration ability, which was proved in the test on four benchmark functions.
Keywords :
particle swarm optimisation; collaborative optimization; dynamic particle population based particle swarm optimization; global search ability; globe exploration ability; multiswarm based hybrid optimization algorithm; particle population; Algorithm design and analysis; Analytical models; Attenuation; Benchmark testing; Collaboration; Computational modeling; Convergence; Evolutionary computation; Heuristic algorithms; Particle swarm optimization; dynamic particle population; particle swarm optimization algorithm; population; swarm diversity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Modeling and Simulation, 2010. ICCMS '10. Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-1-4244-5642-0
Electronic_ISBN :
978-1-4244-5643-7
Type :
conf
DOI :
10.1109/ICCMS.2010.186
Filename :
5421517
Link To Document :
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