基于遗传粒子群算法的冷连轧轧制规程优化设计  

Optimization of Rolling Schedule in Tandem Cold Mills Based on GAPSO Algorithm

作　　者：车海军[1] 刘畅[1] 孙晓娜[1] 杨景明[1] 

机构地区：[1]燕山大学工业计算机控制工程河北省重点实验室,河北秦皇岛066004

出　　处：《轧钢》2009年第1期22-25,共4页Steel Rolling

摘　　要：选取等相对负荷为轧制规程的目标函数,令轧制力、轧制功率、轧制力矩、轧制速度等参数满足一定约束条件,采用罚函数法将有约束条件转为无约束条件。用遗传粒子群算法对目标函数进行优化,求得最优解。该混合算法集合了遗传算法全局搜索能力强,粒子群算法局部搜索能力强,收敛速度快的特点。使得各机架功率合理分配,设备能力充分发挥,生产效率提高。This paper adopts equal relatively load as objective function, makes the rolling force, rolling power, rolling torque,speed and other parameters to meet certain restrictive conditions. SUMT algorithm is used to change constraints to non-binding conditions. GAPSO algorithm is applied to optimize the objective function to obtain the optimal solution. This hybrid algorithm takes both advantage of GA and PSO algorithm, integrates global searching ability with high convergence speed. It makes the reasonable distribution of tandem cold rolling power,gives full play to equipment capacity and improves the production efficiency.

关 键 词：冷连轧 轧制规程优化 遗传粒子群算法 罚函数 

分 类 号：TG335.12[金属学及工艺—金属压力加工]