Multi-objective optimization for leaching process using improved two-stage guide PSO algorithm

A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process. The model is proved to be effective by experiment. Afterwards, the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model. A two-stage guide multi-objective particle swarm optimization (TSG-MOPSO) algorithm was proposed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well. Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice. The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO, and can improve the current manual solutions significantly. The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%, respectively.