基于改进多目标遗传算法的连铸二冷过程优化

doi:10.12068/j.issn.1005-3026.2019.05.010

东北大学学报:自然科学版 ›› 2019, Vol. 40 ›› Issue (5): 658-662.DOI: 10.12068/j.issn.1005-3026.2019.05.010

基于改进多目标遗传算法的连铸二冷过程优化

翟莹莹¹，厉英²，敖志广¹

(1. 东北大学计算机科学与工程学院，辽宁沈阳110169; 2. 东北大学冶金学院，辽宁沈阳110819)

收稿日期:2018-04-20 修回日期:2018-04-20 出版日期:2019-05-15 发布日期:2019-05-17
通讯作者: 翟莹莹
作者简介:翟莹莹(1984-)，女，黑龙江望奎人，东北大学讲师，博士；厉英(1963-)，女，安徽合肥人，东北大学教授，博士生导师.
基金资助:
中央高校基本科研业务费专项资金资助项目(N171603015)； “十三五”国家重点研发计划项目(2017YFB0304200).

Optimization of Continuous Casting Secondary Cooling Based on An Enhanced Multi-objective Genetic Algorithm

ZHAI Ying-ying¹， LI Ying²， AO Zhi-guang¹

1. School of Computer Science & Engineering， Northeastern University， Shenyang 110169， China; 2. School of Metallurgy， Northeastern University， Shenyang 110819， China.

Received:2018-04-20 Revised:2018-04-20 Online:2019-05-15 Published:2019-05-17
Contact: LI Ying
About author:-
Supported by:
-

摘要/Abstract

摘要： 采用一种改进的多目标遗传算法对二冷工艺进行优化.改进的多目标遗传算法应用概率法选取选择算子，根据适应度值来动态计算交叉和变异概率，能够得到更好的全局最优解，提高算法精度和整体性能.在基于凝固传热模型的二冷优化过程中，采用变间距差分法离散求解传热方程，对比粒子群算法、多目标遗传算法，改进的多目标遗传算法搜索效率高，得到的价值函数最小.在实际生产中，采用优化后的二冷工艺，使得总用水量减少约10%，提高了铸坯质量，达到了节能降耗的要求.

关键词: 连铸, 二冷工艺, 凝固传热模型, 多目标遗传算法, 冶金准则

Abstract: An enhanced multi-objective genetic algorithm is adopted to optimize secondary cooling process， which uses the probability method to select the operator and calculates crossover and mutation probability dynamically according to the fitness value. A better global optimal solution is achieved and the algorithm precision and overall performance improve greatly. In the secondary cooling optimization process， the model based on solidification heat transfer is solved by the variable spacing difference method. Compared to particle swarm algorithm and the traditional multi-objective genetic algorithm， the enhanced multi-objective genetic algorithm has the highest search efficiency and the minimum value function. In industrial applications， the optimized secondary cooling process can reduce the total consumption of water by 10% and improve the quality of casting billet， which meet the requirements of energy saving and consumption reduction.

Key words: continuous casting, secondary cooling technology, solidification and heat transfer model, multi-objective genetic algorithm, metallurgical criteria

中图分类号:

T391.4

翟莹莹，厉英，敖志广. 基于改进多目标遗传算法的连铸二冷过程优化[J]. 东北大学学报:自然科学版, 2019, 40(5): 658-662.

ZHAI Ying-ying， LI Ying， AO Zhi-guang. Optimization of Continuous Casting Secondary Cooling Based on An Enhanced Multi-objective Genetic Algorithm[J]. Journal of Northeastern University Natural Science, 2019, 40(5): 658-662.

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基于改进多目标遗传算法的连铸二冷过程优化

Optimization of Continuous Casting Secondary Cooling Based on An Enhanced Multi-objective Genetic Algorithm

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