Yasir Mehmood, Waseem Shahzad
Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 91-103, 2019, DOI:10.31209/2018.100000017
Abstract Particle swarm optimization (PSO) algorithm is a global optimization technique
that is used to find the optimal solution in multimodal problems. However, one
of the limitation of PSO is its slow convergence rate along with a local trapping
dilemma in complex multimodal problems. To address this issue, this paper
provides an alternative technique known as ACPSO algorithm, which enables to
adopt a new simplified velocity update rule to enhance the performance of PSO.
As a result, the efficiency of convergence speed and solution accuracy can be
maximized. The experimental results show that the ACPSO outperforms More >
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