用遗传算法进行多流股换热器网络综合的研究

建立了多流股换热器网络综合数学模型，该模型改进了文献中等温混合的不合理假设。多流股换热器网络综合问题本质上是一个混合整数非线性规划问题(MINLP)，这类问题的非凸非线性的特性使得目标函数存在多个局部最优解。传统的基于梯度的搜索方法在处理这类问题时由于计算规模庞大且极易陷于局部最优解而不再适用，而遗传算法却为解决这类问题提供了很有希望的一个方向。因而对遗传算法求解多流股换热器网络综合问题进行了研究，提出了可以自动产生可行的多流股换热器网络的方法策略，最后通过两个例题说明所提方法是可行的。

Study on Multi-stream Heat Exchanger Networks Synthesis with Genetic Algorithm

Different from the assumption of isothermal mixing of stream splits and thus linearity constraints in literature, non-isothermal mixing was proposed, and a corresponding mathematical model for multi-stream heat exchanger networks synthesis problem was setup. The multi-stream heat exchanger networks synthesis problem (HENS) can be formulated as a mixed integer nonlinear programming model. Its nonconvexity nature leads to existence of more than one optimum and computation difficulty for traditionally algorithms to find the global optimum. Compared with other deterministic algorithms, GA provides a promising approach to tackle this problem. A novel method for the synthesis of multi-stream heat exchanger networks based on genetic algorithms (GAs) using the stage-wise superstructure was presented. And an automatic generation strategy for multi-stream heat exchanger networks was proposed to successfully provide initial solution populations for the genetic evolution. The performance of the proposed GA approach and the automatic network generation strategy were demonstrated through examples and the obtained solutions were compared well with those available in literature.