应用遗传算法优化设计壳管式换热器

Optimization design of shell-and-tube heat exchangers based on genetic algorithm

针对壳管式换热器传统设计方法繁杂且结果又不能满足最佳经济费用的缺点,引入遗传算法对壳管式换热器进行设计。建立了相应的数学模型并以设备总费用为目标函数,对换热器进行优化设计。利用遗传算法智能及多点搜索等特性,不断地迭代优化变量,在优化变量值和约束条件范围内,得到最小目标函数的设计结果。采用了2个实际算例进行测试,结果显示在满足换热性能的前提下,优化后总费用都有降低,降幅分别为18.2%,7.98%。

Genetic algorithm（GA） is used for the optimal design of shell-and-tube heat exchangers due to the fact that traditional designs for shell-and-tube heat exchangers are complicated and uneconomical.To optimize the design of heat exchangers,mathematical models are established and the total costs are used as the objective function.Taking advantage of GA＇s intelligent and multi-searching characteristics,researchers continuously iterate optimization variables and then obtain the minimum objective function of the design results within the optimal variable values and constraints.Two practical heat exchangers are used to test the research results.The Optimization results show that the optimized total costs have decreased by 18.2% and 7.98% respectively,which can also satisfy the heat transfer performance.Moreover,the results show that the design based on GA for shell-and-tube heat exchangers can significantly improve the economic efficiency of heat exchangers and thus can be applied to engineering practice.