摘要
针对铜闪速熔炼配料过程人工计算配比的主观性和局限性,基于配比影响因素分析,建立综合考虑品位、成本、库存的配料优化模型;引入"软约束"调整模型的约束边界,改善优化问题求解的可行性;并提出以单变量编码的交叉变异来确定整体决策向量的改进遗传算法进行寻优,以克服多维变量编码时可能导致搜索空间剧增的缺陷。最后结合工业运行数据进行配比优化计算,优化结果表明该方法在满足熔炼工艺要求基础上,能有效降低杂质含量和生产成本。
Considering the subjectivity and limitation of manual computation in the burden process of copper flash smelting, an optimal model was built up based on the analysis of major influencing factors, which integrated the component, the cost and the storage of copper concentrates. The boundaries of constraints were adjusted according to the conception of soft constraint to improve the feasibility of the optimal problem, and an improved genetic algorithm was proposed to get the optimum solution, where a vector was decided by crossover and mutation of a single variable coding, such that the large-scale search space was avoided owing to the multi-dimensional coding. Finally the computation results with practical running data show that the application of the optimal model will reduce the cost, lower impurities and also benefit to steady production.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2008年第8期2152-2155,共4页
Journal of System Simulation
基金
国家自然科学基金(60574030
60634020)
教育部新世纪优秀人才支持计划(NCET-04-0751)
高校博士点基金(2005053016)
关键词
铜闪速熔炼
配料优化
软约束
改进遗传算法
copper flash smelting
burden optimization
soft constraint
improved genetic algorithm
