Dynamic multi-objective optimization arising in iron precipitation of zinc hydrometallurgy
Dynamic multi-objective optimization arising in iron precipitation of zinc hydrometallurgy
复制标题
湿法炼锌铁沉淀的动态多目标优化
DOI：
10.1016/j.hydromet.2017.08.007
复制
发表时间：
2017-11-01
期刊：
影响因子：
4.7
通讯作者：
Gui, Weihua
中科院分区：
文献类型：
--
作者：
Han, Jie;Yang, Chunhua;Gui, Weihua
The additions of oxygen and zinc oxide for the goethite process determine the cost and efficiency of the iron precipitation process. As the two production targets (cost and efficiency) are conflicting and the chemical reaction is a continuous process that changes over time, the amounts of additive need to be dynamically optimized to satisfy the requirement of industrial application. In this paper, a discretization method based on control variables and control intervals is proposed to transform the dynamic optimization problem to a nonlinear mathematical programming problem. Then, a multi-objective optimization approach based on the state transition algorithm and constrained nondominated sorting is proposed to find the Pareto optimal solutions. Finally, an evaluation mechanism is proposed to obtain the best solution for industrial applications. The results from a series of simulation experiments show the effectiveness of the proposed approach, e.g. the daily average additions of oxygen and zinc oxide are decreased by 778.0854 m(3) and 4.9013 t, respectively.
