Title :
Application of Simulated Annealing Particle Swarm Optimization Algorithm in Power Coal Blending Optimization
Author_Institution :
Dept. of Mech. Eng., North China Electr. Power Univ., Baoding
Abstract :
The particle swarm optimization algorithm is easily trapped into local optimization. In order to improve its performance , The simulated annealing operation was introduced into PSO. The hybrid algorithm combines the fast search optimum ability of PSO with probability jump property of SA. It can maintain the individual diversity and restrain the degenerate phenomenon. The experiment results compared with genetic algorithm demonstrate that the proposed algorithm can search for global optimal solution more reliably and faster, and the power coal blending optimization can be efficiently solved with higher quality.
Keywords :
coal; genetic algorithms; particle swarm optimisation; probability; simulated annealing; degenerate phenomenon; fast search optimum ability; genetic algorithm; global optimal solution; hybrid algorithm; local optimization; particle swarm optimization algorithm; power coal blending optimization; probability jump property; simulated annealing; Birds; Boilers; Costs; Electronic mail; Fuels; Maintenance; Mechanical engineering; Mechanical factors; Particle swarm optimization; Simulated annealing;
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
DOI :
10.1109/WiCom.2008.1250