中南大学学报（自然科学版）2012，Vol.43Issue(1)：184-188,5.
改进差分进化算法在铝电解多目标优化中的应用
An improved hybrid differential evolution algorithm used for multi-objective optimization of aluminum electrolysis
摘要
Abstract
An improved hybrid differential evolution algorithm for multi-objective optimization problems was proposed. To increase the convergence speed, differential evolution and particle swarm optimization were combined, and then multi-swarm evolutionary strategy was introduced to maintain the diversity of the Pareto solutions. A multi-objective optimization model of aluminum electrolysis cell was built based on the mechanism and was resolved based on the improved algorithm. The simulation results show that the DC power consumption is 14.03 MWh/t by using the improved algorithm, which is 1.45% lower than consumption using NSGA-II and is 1.75% lower than the consumption by using DE algorithm. The results indicate the proposed algorithm can effectively improve the performance of traditional evolution algorithms.关键词
差分进化算法/铝电解/多目标优化/粒子群优化/多种群进化Key words
differential evolution algorithm/ aluminum electrolysis/ multi-objective optimization/ particle swarm optimization/ multi-swarm evolution分类
信息技术与安全科学引用本文复制引用
郭俊,桂卫华,阳春华..改进差分进化算法在铝电解多目标优化中的应用[J].中南大学学报（自然科学版）,2012,43(1):184-188,5.基金项目
国家“十一五”国家支持计划项目(2009BAE85B00) （2009BAE85B00）
