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.

关键词： Particle Swarm Optimization Algorithm (MOPSO) Multi-objective Optimization Problem (MOP) Power Supply Curve Optimization Weighted Pheromone Sharing Mechanism Position Migration and Clustering Population Compression

作者: Feng Lin Mao Zhizhong Yuan Ping You Fuqiang

作者单位: Northeastern University, Shenyang 110819, China

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 867-871

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）