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A Novel Computational Strategy to Enhance the Ability of Elaborate Search by Entire Swarm to Find the Best Solution in Optimization of AMCs

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Abstract:

Al 6061 alloy matrix reinforced with the coated B₄C particles have been used to investigate the accuracy of a novel optimization method. Population-based optimization was inspired by the swarming behavior as is displayed by a social behavior being influenced by other individuals. The present article focuses on a method of re-evaluating a number of randomly chosen sentry particles to detect the change of environments. A comprehensive population-based optimization method was developed to optimize the mechanical and tribological properties in metal matrix composites using Multi-strategy ensemble particle swarm optimization. In this method, the particles are divided into two parts which are considered to play different roles in searching for dynamic environments by using different strategies. The global best used in part one is the best solution found by all particles, both in part one and part two.

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Defects and Diffusion in Semiconductors XIV

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Periodical:

Defect and Diffusion Forum (Volume 332)

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27-33

DOI:

https://doi.org/10.4028/www.scientific.net/DDF.332.27

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Online since:

December 2012

Authors:

Mohsen Ostad Shabani, Ali Mazahery

Keywords:

Mechanical Property, Modeling, Optimization

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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