摘要
针对金氰化浸出过程,建立了生产成本最小为目标的优化模型,采用序列二次规划(SQP)算法与改进粒子群算法(PSO)相结合对模型进行求解,并通过对比优化前后金浸出率,验证了改进PSO-SQP算法的可行性。结果表明:相比于常规方法,改进PSO-SQP算法可有效降低迭代次数和生产成本;浸出过程优化后的金浸出率达97.03%,比优化前提高2.47%。改进PSO-SQP算法对金浸出过程优化控制具有一定的实用价值。
Aim at the gold cyanide leaching process,an optimization model aiming at the minimum production cost was established.The model was solved by the combination of sequential quadratic programming and improved particle swarm optimization algorithm.The feasibility of the improved PSO-SQP algorithm was verified by comparing the gold leaching rate before and after optimization.The results show that compared with the conventional method,the improved PSO-SQP algorithm can effectively reduce the number of iterations and the cost of production.The gold leaching rate can reach 97.03%after optimization,2.47%higher than before optimization.The improved PSO-SQP algorithm has certain practical value for the optimization control of gold leaching process.
作者
李伟
LI Wei(Henan Logistics Vocational College,Xinxiang 453000,China)
出处
《湿法冶金》
CAS
北大核心
2023年第3期317-321,共5页
Hydrometallurgy of China
关键词
金
浸出
序列二次规划(SQP)
粒子群算法(PSO)
优化
生产成本
gold
leaching
sequential quadratic programming(SQP)
particle swarm optimization(PSO)
optimization
production cost
