针对于启发式算法应用于换热网络优化时，后期由于种群多样性消失或其他原因导致年综合费用难以进一步下降的问题，提出了一种结构进化增强策略。该策略在一般启发式算法的整型变量优化中，通过将换热单元的生成与消去分开处理，先以一定概率随机地在网络中生成若干换热单元，再在连续变量优化的过程中实现换热单元的消去，提升网络结构变异能力。最后，将该策略与强制进化随机游走算法(random walk algorithm with compulsive evolution,RWCE)相结合形成一种新的混合算法（ESE-RWCE）。算例研究表明，ESE-RWCE算法相比于RWCE算法实现了全局搜索性能的提升。

When the heuristic algorithm is applied to heat exchanger network optimization,it is difficult to further reduce the cost in the later period due to the loss of population diversity or any other reasons.In this paper,an enhanced structure evolution strategy is proposed.The generation and elimination of the heat exchangers are separated in the optimization of integer variable of the heuristic algorithm.First of all,a number of heat exchangers are randomly generated in the network with a certain probability,and then the heat exchangers are eliminated in the process of optimizing the continuous variables to achieve the improvement of the network structure evolution ability.Eventually,the strategy is combined with RWCE algorithm to form a new hybrid algorithm (ESERWCE).The case studies show that the ESERWCE algorithm,compared to RWCE algorithm,is capable of obtaining better optimization efficiency and accuracy.

TK124

国家自然科学基金（51176125）；上海市科委部分地方院校能力建设计划（16060502600）