Abstract:Based on the published results,the methods and algorithms for the optimization of the raw materials blending in sinter process were comparatively analyzed. The results confirmed that linear programming was a convenient and efficient algorithm to solve the common models with small-scale calculations,while genetic algorithm,particle swarm optimization and ant colony algorithm can handle with the complicated models with large-scale calculations. Neural net algorithm was a power method to predict production results with big data. The expert system coupled with neutral net can solve many complicated problems in industrial operation process. The goal of raw materials blending in sinter process should be the lowest cost of hot metal and maintain the quality of sinter in the future.
唐庆利,张建良,李克江,孙敏敏,钟建波,刘征建. 烧结配料优化方法及算法对比分析[J]. 中国冶金, 2017, 27(5): 13-18.
TANG Qing-li,ZHANG Jian-liang,LI Ke-jiang,SUN Min-min,ZHONG Jian-bo,LIU Zheng-jian. Comparative analysis on methods and algorithms for optimization of raw materials blending in sinter process. China Metallurgy, 2017, 27(5): 13-18.