Abstract
The mechanism of particle swarm optimization algorithm is studied, and one can draw the conclusion that the best particle found by the swarm falling into local minima is one of the main reasons for premature convergence. Therefore, an improved particle swarm optimization algorithm is proposed. This algorithm selects the best particle with roulette wheel selection method, so premature converging to local optima is avoided. At last, the improved particle swarm optimization algorithm is applied to optimization of time-sharing power supply for zinc electrolytic process. Simulation and practical results show that the global search ability of IPSO is improved greatly and optimization of time-sharing power supply for zinc electrolytic process can bring about outstanding economic benefit for plant.
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Foundation item: Project (2002CB312200) supported by the National Key Research 973 Program of China
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Li, Yg., Gui, Wh., Yang, Ch. et al. Improved PSO algorithm and its application. J Cent. South Univ. Technol. 12 (Suppl 1), 222–226 (2005). https://doi.org/10.1007/s11771-005-0403-4
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DOI: https://doi.org/10.1007/s11771-005-0403-4
Key words
- particle swarm optimization
- premature convergence
- roulette wheel
- zinc electrolytic process
- time-sharing power supply