Modeling and Optimization of Water Distribution in Mineral Processing considering Water Cost and Recycled Water

Abstract

Reducing mineral processing water costs and freshwater consumption is a challenging task in the mineral processing water distribution (MPWD). The work presented in this paper focuses on two aspects of the MPWD optimization model and the MPWD optimization method. To achieve MPWD optimization effectively, a nonlinear constrained multiobjective model is built. The problem is formulated with two objectives of minimizing the mineral processing water costs and maximizing the amount of recycled water. In this paper, an optimization method named enhancing the multiobjective artificial bee colony (EMOABC) algorithm is proposed to solve this model. The EMOABC algorithm uses four strategies to obtain the Pareto-optimal solutions and to achieve the MPWD optimal solutions. With the three benchmark functions, the EMOABC algorithm outperforms the other two widely used algorithms in solving complex multiobjective optimization problems. The EMOABC algorithm is then applied to two cases. Results have shown that the proposed algorithm has the ability to solve the MPWD optimization model. The developed model and the proposed algorithm provide decision support for the actual MPWD problem.