Abstract
Abstract:
To avoid the bored try and error method of finding a set of
parameters of Particle Swarm Optimization (PSO) and achieve good
optimization performance, it is desired to get an adaptive optimization method
to search a good set of parameters. A nested optimization method is proposed in
this paper and it can be used to search the tuned parameters such as inertia
weight, acceleration coefficients c1 and c2, and so on. This method considers
the cask theory to achieve a better optimization performance. Several famous
benchmarks were used to validate the proposed method and the simulation
results showed the efficiency of the proposed method.
Originally presented at Fourth International Conference on Swarm Intelligence (ICSI 2013), Harbin, China, 12-15, June, 2013.