A Modified Particle Swarm Optimization Algorithm with Cases Studies

Abstract:

Article Preview

s paper presents a hybrid algorithm, the “particle swarm optimization with simulated annealing behavior (SA-PSO)” algorithm, which combines the advantages of good solution quality in simulated annealing and fast calculation in particle swarm optimization. As stochastic optimization algorithms are sensitive to its parameters, this paper introduces criteria in selecting parameters to improve solution quality. To prove the usability and effectiveness of the proposed algorithm, simulations are performed using 20 different mathematical optimized functions of different dimensions. The results made from different algorithms are then compared between the quality of the solution, the efficiency of searching for the solution and the convergence characteristics. According to the simulation results, SA-PSO obtained higher efficiency, better quality and faster convergence speed than other compared algorithms.

Info:

Periodical:

Advanced Materials Research (Volumes 268-270)

Edited by:

Feng Xiong

Pages:

823-828

DOI:

10.4028/www.scientific.net/AMR.268-270.823

Citation:

C. C. Kuo et al., "A Modified Particle Swarm Optimization Algorithm with Cases Studies", Advanced Materials Research, Vols. 268-270, pp. 823-828, 2011

Online since:

July 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.