An improved multi-objective particle swarm optimization algorithm and its application in EAF steelmaking process

摘要

An efficient improved multi-objective particle swarm optimization algorithm based weighted pheromone sharing mechanism (PM-MOPSO) approach for solving the power supply curve of electric arc furnace(EAF) steelmaking process is presented in this paper. In PM-MOPSO algorithm, the weighted pheromone sharing mechanism coordinates specific gravity among the optimal solutions; the position migration accelerates algorithm convergence speed; the clustering population compression maintains population diversity. Finally, the application shows that it reduces the electric energy consumption, shortens smelting time and improves lifetime of the furnace lining and cover. The result expresses that the algorithm is effective.