基于遗传算法的烧结配料综合优化研究

钢铁, 2007, 42(4): 12-0.

基于遗传算法的烧结配料综合优化研究

吕学伟 , 白晨光 , 邱贵宝 , 欧阳奇 , 黄玉明

1.1. 重庆大学材料科学与工程学院，重庆 400044；2. 重庆钢铁（集团）公司产业有限公司，重庆 400084

1.1. College of Material Science and Engineering, Chongqing University, Chongqing 400044, China

2. 2. Industry Co., Ltd. of Chongqing Iron and Steel (Group) Corp., Chongqing 400084, China

关键词：配料优化;遗传算法;多元逐步回归;烧结矿

Research on Sintering Burdening Optimization Based on Genetic Algorithm

L Xuewei , BAI Chenguang , QIU Guibao , OUYANG Qi , HUANG Yuming

Keywords： burdening optimization;genetic algorithm;stepwise regression;sinter

运用遗传算法和逐步回归分析的方法建立烧结配料优化模型，对重钢烧结配料优化，并进行了实验验证和分析。结果表明：优化配料后的烧结矿化学成分和物理性能均满足生产的要求，在稳定各项指标的前提下，每吨烧结矿原料成本降低14.7元。应用遗传算法，可以解决线性规划等方法所不能处理的问题，实现更快、更全面的优化烧结配料。

A burdening optimization model for sintering based on GA (Genetic Algorithm) and stepwise regression, was established and proved at Chongqing Iron and Steel Co., Ltd. The results indicated that chemical composition and physical properties of sinters meet the requirements of production, the cost of sinters was decreased by 14.7 RMB/t. The problems in burdening that could not be solved with LP (Linear Programming) or other algorithms can be solved with GA.

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