摘要
针对目前钢铁企业热送热装(HCR)板坯库入库管理的实际需求,以板坯库有限HCR储位和垛位选择原则为约束,建立了一种基于铸轧作业计划协同优化的板坯入库决策模型.实现了需入库的HCR板坯批次的全局优化运算,算法可快速优化出板坯入库垛位和铸机板坯产出序.对于建立的模型,构造了一种遗传模拟退火算法进行求解,该算法充分发挥了遗传算法良好的全局搜索能力和模拟退火算法有效避免陷入局部极小的优点.对实际问题的求解结果表明,建立的模型和算法正确可行,为HCR板坯入库选择合理垛位提供了一种行之有效的解决方法.
According to the need of today＇s steel industry for HCR （hot charge rolling） slab yard entry management, a slab location decision model is presented. The model is based on the collaborative optimization of casting and rolling plans and is subject to the limited slab yard storage and the rules of HCR pile position selection. It is a general optimal operation for the HCR slab batch needing to enter the slab yard, and can quickly optimize the pile position of each slab and the casting sequence of the slab batch. A genetic simulated annealing algorithm （GSA） is applied to the model. The algorithm makes full use of the excellent global searching ability of genetic algorithm （GA）, and takes the advantage of simulated annealing algorithm （SA） which can efficiently avoid local minimum. The proposed model and algorithm have been used to solve the practical problems, and the results show they are feasible and effective, providing an effective solution for the selection of optimal pile position for each HCR slab.
出处
《信息与控制》
CSCD
北大核心
2008年第5期529-533,共5页
Information and Control
基金
国家自然科学基金资助项目(70371507)
关键词
热送热装
板坯入库决策
优化
遗传算法
模拟退火算法
hot charge rolling （HCR）
slab location decision
optimization
genetic algorithm
simulated annealing algorithm
