A Modified Particle Swarm Optimization Algorithm with Cases Studies

Cheng Chien Kuo; Hung Cheng Chen; Teng Fa Taso; Chin Ming Chiang

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

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 268-270A Modified Particle Swarm Optimization Algorithm...

A Modified Particle Swarm Optimization Algorithm with Cases Studies

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 268-270)

Pages:

823-828

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.268-270.823

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Online since:

July 2011

Authors:

Cheng Chien Kuo, Hung Cheng Chen, Teng Fa Taso, Chin Ming Chiang

Keywords:

Genetic Algorithm (GA), Particle Swarm Optimization Algorithm (PSO), Simulated Annealing (SA)

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