摘要
概括混合型通风网络优化模型,归纳混合型通风网络风量最优分配和风流最优调控两步法优化基本框架。首先,在满足矿井通风风量需求的基础上,实现风量分配优化。然后,结合矿井通风网络实际调风需求,引入遗传算法随机产生动态网络的邻接矩阵,使用附有条件的最小支撑树算法求解部分余树弦(调风地点)约束下的最小支撑树和独立回路矩阵,根据回路矩阵计算通风网络余树弦风阻调节值,在通风总功率和约束条件基础上构建广义最小化目标函数,依此对调节方案进行评价,使用遗传算法中的进化算子对调节方案编码实施进化操作,最后通过迭代得到满意解。研究结果表明:两步法思想简化混合型通风网络优化问题,解决调风地点约束的通风网络优化问题,执行效率高,能够解决较大规模的通风网络优化问题。
The model of mixing ventilation networks optimization was generalized,and the basic frame of two step way on mixing ventilation networks optimization was summed up.Firstly,the ventilation volume distribution optimization of min ventilation networks was carried out in the condition of mine ventilation volume demand,and then the adjacency matrix of dynamic networks was initialized on random according to genetic algorithm thought,in accordance with the demand of mine adjusting ventilation,the minimum spanning tree of dynamic network with location restriction about some remaining tree branches was searched by the way of minimum spanning tree algorithm confined in conditions,independence circuit matrix was calculated,and then the ventilation resistance adjusting values of remaining tree branches were calculated by circuit matrix.The generalized objective function was set up in the sum ventilation power and restriction conditions,the ventilation resistance adjusting schemes were evaluated by the generalized objective function,and schemes codes were evolved by genetic operator.Finally,the satisfaction ventilation resistance adjusting schemes was attained by iterative.The results show that the algorithm reduces the complexity solving mixing ventilation networks optimization problem by two step way.The algorithm deals with adjust location restriction very well.The algorithm is very good in executing efficiency and can solve large-scale mixing ventilation networks optimization problem.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第9期2729-2736,共8页
Journal of Central South University:Science and Technology
基金
陕西省自然科学基金资助项目(2009JM7007)
陕西省教育厅专项科研计划项目(08JK354)
关键词
通风网络优化
遗传算法
两步法
最优化理论
ventilation networks optimization
genetic algorithm
two steps way
optimization theory
