摘要
针对罩式炉退火工艺中的钢卷装炉优化组合问题,建立了以最小化装炉计划数和钢卷总加热时间为目标的数学模型,提出了一种自适应遗传算法和蚁群算法相结合的两阶段智能优化算法.该算法按照先优化钢卷装炉计划数后优化钢卷总加热时间的顺序求解该问题.通过现场实际生产数据进行仿真表明,提出的装炉优化组合模型优化效果明显,提高了退火车间的钢卷装炉效率.
In order to optimize the combination stacking of steel coils in bell-type batch annealing process, a mathematical model is proposed to minimize the number of steel coils stacks and the total heating treatment time. A two-stage intelligent optimization algorithm based on adaptive genetic algorithm and ant colony algorithm is constructed. The algorithm solves the problem with two steps: the number of steel coil stacks is optimized firstly, and secondly the total coil stack heating hours is optimized. A simulation experiment with practical production data shows that the proposed combination stacking method attains a good optimizing ability, and increases the stacking efficiency of the annealing process.
出处
《信息与控制》
CSCD
北大核心
2009年第2期211-217,共7页
Information and Control
基金
国家863计划资助项目(2007AA04Z156)
国家自然科学基金资助项目(60604026)
关键词
罩式炉退火
装炉组合
自适应遗传算法
蚁群算法
batch annealing
combination stacking
adaptive genetic algorithm
ant colony algorithm