Dynamic multi-objective optimization and fuzzy AHP for copper removal process of zinc hydrometallurgy

In order to improve the production efficiency and reduce the production cost of copper removal process (CRP), it is necessary to control the addition rate of zinc powder in CRP. In this study, the control of zinc powder addition rate is modeled as a dynamic multi-objective optimization problem (DMOP). A Pareto set which contains multiple control schemes is obtained by using multi-objective state transition algorithm based on decomposition, and then a new fuzzy multi-criteria decision-making (MCDM) is proposed to select the best control scheme. In the MCDM, according to the real-world requirements of CRP, four criteria are adopted to evaluate these schemes, and the fuzzy analytic hierarchy process (AHP) is adopted to determine the criteria weights according to a fuzzy comparison matrix. Furthermore, the nonlinear mixed integer programming model is established to guarantee consistency of the fuzzy comparison matrix. Experimental results of an industrial plant in China have demonstrated the effectiveness and superiority of the proposed method in terms of the cost, reaction rate, stability of outlet copper ion concentration, etc.