Particle Swarm Optimization with Adaptive Inertia Weight and its Application in Optimization Design

Xiao Lei Wang; Yu Yang; Qiang Zeng; Jin Qiang Wang

doi:10.4028/www.scientific.net/AMR.97-101.3484

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Design and Analysis of MEMS-Based Actuator
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Research on Virtual Design and Simulation System for Manipulators of Multi-Degree of Freedom
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Research on Comfort Evaluation Method of Tool Handles
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 97-101Particle Swarm Optimization with Adaptive Inertia...

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.

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Periodical:

Advanced Materials Research (Volumes 97-101)

Pages:

3484-3488

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.97-101.3484

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Online since:

March 2010

Authors:

Xiao Lei Wang, Yu Yang, Qiang Zeng, Jin Qiang Wang

Keywords:

Aggregation Degree, Evolution Speed, Optimization Design, Particle Swarm Optimization Algorithm (PSO), Penalty Function

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