摘要
建立了矿井通风系统网络优化的非线性规划数学模型,并用遗传算法来求解该优化模型.使用罚函数法对优化模型所包含的约束方程进行转化和处理,使之适用于遗传算法.罚函数的形式采用不可微精确罚函数,并在惩罚参数的选择上参考了模拟退火算法的一些优点,设计出一种动态罚函数.应用遗传算法对一个简单通风网络的优化模型进行求解.结果表明:优化后通风系统总能耗降低了7.78 kW,其下降幅度约为3%.
A general non-linear mathematics programming model for optimizing the mine ventilation network was established and solved by genetic algorithm. The penalty function method was used in treating and transforming the constraint equations contained in the optimizing model so as to be suitable for the genetic algorithm. Non-differentiable accurate penalty functions were chosen in treating the constraint equation and the advantages of simulated annealing algorithm was used for reference in determining penalty parameters. On the basis of this, a dynamic penalty function was designed. Then the genetic algorithm was used to solving the optimized model for a simple ventilation network. The result shows that the overall energy consumption of the optimized ventilation system has a decrease of 7.78 kW, with a decreasing rate of 3%.
出处
《中国矿业大学学报》
EI
CAS
CSCD
北大核心
2007年第6期789-793,共5页
Journal of China University of Mining & Technology
基金
国家自然科学基金资助项目(50534090
50574093)
国家重点基础研究发展(973)计划(2005cb221506)
国家十五重点科技攻关项目(2005BA813B07)
关键词
遗传算法
矿井通风网络
优化模型
罚函数
模拟退火算法
genetic algorithms
mine ventilation network
optimization model
penalty functions
simulated annealing algorithms
