摘要
在换热网络超结构及其数学模型的基础上,提出了换热网络优化的蒙特卡罗遗传混合算法,利用蒙特卡罗方法在解空间进行全局搜索,得到最佳换热匹配,由此引入遗传算法对网络优化问题中的连续性变量进一步优化,降低换热网络年综合费用。实例表明,应用蒙特卡罗遗传混合策略能在保证算法的全局搜索能力的前提下,提高换热网络优化效率,并能使换热匹配更加合理,减少加热器和冷却器的投入,降低网络的综合费用。
Based on the analysis of heat exchanger network(HEN)superstructure and its mathematic model,HEN optimization Monte Carlo genetic algorithm is put forward.The optimal matching can be obtained by Monte Carlo.Then continuous variables in the network optimization are further optimized by genetic algorithm,thus reducing the annual overall cost of HEN.The case study shows that-Monte Carlo genetic algorithm can improve the optimization efficiency of HEN on the premise of guaranteeing the overall search ability.The heat exchanger matching is made more rational and less investment on heater and cooler is required,thus reducing the overall cost of HEN.
出处
《石油机械》
北大核心
2007年第5期19-22,70,共4页
China Petroleum Machinery
基金
国家自然科学基金项目(20406011)
上海市重大科技攻关项目(05dz12028)
上海市重点学科项目(T0503)
关键词
换热网络
蒙特卡罗法
遗传算法
优化
heat exchanger network,Monte Carlo method,genetic algorithm,optimization
