基于自适应蚁群算法的艾萨炉铜熔炼配料优化方法

Batching Optimization Method for ISA Furnace during Copper Smelting Based on Adaptive Ant Colony Algorithm

针对艾萨炉铜熔炼过程配料优化问题,提出了基于自适应蚁群算法的艾萨炉铜熔炼过程配料智能优化方法.该方法首先分析了艾萨炉铜熔炼过程中工艺配料特点,以成本为优化目标,综合考虑工艺、质量、库存等多约束条件,采用自适应蚁群学习算法,将配料优化问题转化为在各种约束条件下的学习建模问题,借助历史配料数据进行建模,实现配料预测与优化.艾萨炉铜熔炼配料实验结果表明,提出的方法能有效降低生产成本,改进配料系统的效率,比人工方式物料配比有很大的改进.

Referring to the batching optimization problem in ISA furnace during the copper smelting process,the intelligent batching optimization method for the ISA furnace in copper smelting process is put forward,which is based on the adaptive ant colony algorithm.The batching characteristics of ISA furnace in copper smelting process are firstly analyzed,taking cost as the optimization target,integrating technology,quality and inventory as constraints and using the adaptive ant colony algorithm.This method turns the ingredients optimization problem into learning modeling problem under a variety of constraints.The historical batching data are adopted in modeling to realize batching prediction and optimization.It is shown through the ISA furnace batching experiment that the proposed method reduces production cost effectively,improves the efficiency of batching system,and has a significant improvement compared with the artificial material ratio.