Title :
A Novel Atmosphere Clouds Model Optimization Algorithm
Author :
Gao-wei, Yan ; Zhanju, Hao
Author_Institution :
Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China
Abstract :
This paper introduces a novel numerical stochastic optimization algorithm inspired from the behavior of cloud in the natural world, which is designated as Atmosphere Clouds Model Optimization Algorithm (ACMO). And the ACMO algorithm has been tested on a set of benchmark functions in comparison with Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA). The results demonstrate that the proposed algorithm has a certain advantage in solving multimodal functions.
Keywords :
clouds; genetic algorithms; geophysics computing; particle swarm optimisation; stochastic programming; atmosphere clouds model optimization; cloud behavior; genetic algorithm; numerical stochastic optimization; particle swarm optimization; Algorithm design and analysis; Atmospheric modeling; Clouds; Computational modeling; Genetic algorithms; Humidity; Optimization; numerical optimization; evolutionary algorithm; swarm intelligence; cloud model;
Conference_Titel :
Computing, Measurement, Control and Sensor Network (CMCSN), 2012 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4673-2033-7
DOI :
10.1109/CMCSN.2012.117
