Paper Title:
Particle Swarm Optimization with Adaptive Inertia Weight and its Application in Optimization Design
  Abstract

To avoid the premature convergence caused by basic particle swarm optimization(PSO) in resolving engineering optimization design of highly complex and nonlinear constraints, a new particle swarm optimization algorithm with adaptive inertia weight (AIW-PSO) is proposed. In this algorithm, inertia weight is adaptively changed according to the current evolution speed and aggregation degree of the swarm, which provides the algorithm with dynamic adaptability, enhances the search ability and convergence performance of the algorithm. Moreover, penalty function is used to eliminate the constraints. Finally, the validity of AIW-PSO is verified through an optimization example.

  Info
Periodical
Advanced Materials Research (Volumes 97-101)
Edited by
Zhengyi Jiang and Chunliang Zhang
Pages
3484-3488
DOI
10.4028/www.scientific.net/AMR.97-101.3484
Citation
X. L. Wang, Y. Yang, Q. Zeng, J. Q. Wang, "Particle Swarm Optimization with Adaptive Inertia Weight and its Application in Optimization Design", Advanced Materials Research, Vols. 97-101, pp. 3484-3488, 2010
Online since
March 2010
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Price
$32.00
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