Particle Swarm Optimization with Adaptive Inertia Weight and its Application in Optimization Design
Xiao‐Lei Wang, Yang Yu, Qiang Zeng, Jin Qiang Wang · Advanced materials research · 2010
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.