一种双种群协同进化算法在湿法炼锌过程中的应用  

A double population co-evolution algorithm for process of zinc hydrometallurgy

作　　者：熊富强[1] 桂卫华[1] 阳春华[1] 李勇刚[1] 

机构地区：[1]中南大学信息科学与工程学院,长沙410083

出　　处：《控制与决策》2013年第4期590-594,共5页Control and Decision

基　　金：国家自然科学基金项目(60874069);国家863计划项目(2009AA04Z137);湖南省自然科学基金项目(09JJ3122);教育部新世纪优秀人才支持计划项目(NCET-08-0576)

摘　　要：为了求解针铁矿法沉铁过程的多目标协调优化模型,从提高全局寻优能力和解的精度出发,提出一种基于改进全局搜索量子进化算法和局部搜索差分进化算法的双种群协同进化算法.数值仿真验证了该进化算法具有较好的收敛性和求解精度;典型工况的仿真优化结果表明了该多目标协调优化模型指导实际生产的可行性,以及所提出算法的有效性.In order to solve the multi-objective coordination optimization model of iron precipitation by the goethite process, and improve the ability of global optimization and the accuracy of the reconciliation, a double population co- evolution algorithm is proposed, which is composed of improved global searching quantum evolution algorithm based on the sharing function and partial searching difference evolution algorithm based on the individual similarity. Through numerical simulations, it is proved that the evolutionary algorithm has better convergence and solution accuracy. The simulation results of typical operating condition show that the multi-objective coordinated optimization model can guide the actual production feasibly, and the proposed algorithm can solve the model effectively.

关 键 词：湿法冶锌 针铁矿法 协调优化 协同进化 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]