Particle swarm optimization (PSO) algorithm has been developing rapidly and has been applied widely since it was introduced, as it is easily understood and realized. This paper presents an improved particle swarm optimization algo-rithm (IPSO) to improve the performance of standard PSO, which uses the dynamic inertia weight that decreases according to iterative generation increasing. It is tested with a set of 6 benchmark functions with 30, 50 and 150 diff erent dimensions and compared with standard PSO. Experimental results indicate that the IPSO improves the search perfor-mance on the benchmark functions signifi cantly.

A dynamic inertia weight particle swarm optimization algorithm.PDF
Adaptive Particle Swarm Optimization.pdf
Cyber Swarm Algorithms – Improving particle swarm optimization using adaptive memory strategies.PDF

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