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An Artificial Glowworm Swarm Optimization Algorithm Based on Powell Local Optimization Method |
ZHANG Jun Li, ZHOU Yong Quan |
College of Mathematics and Computer Science, Guangxi University for Nationalities, Nanning 530006 |
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Abstract In order to overcome the shortcomings of artificial glowworm swarm optimization (GSO) algorithm including slow convergence speed, easily falling into local optimum value, low computational accuracy and low success rate of convergence, an artificial GSO algorithm based on Powell local optimization method is proposed. It adopts the powerful local optimization ability of Powell method and embeds it into GSO as a local search operator. Experimental results of 8 typical functions show that the proposed algorithm is superior to GSO in convergence efficiency,computational precision and stability.
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Received: 23 July 2010
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