强制进化随机游走算法应用于换热网络优化，具有算法程序简单、结构进化能力强等特点，但种群个体进化后期依然很难找到使年综合费用再次降低的进化方向。鉴于此，分析新生成换热单元最大换热量（Qmax）取值对优化过程及新生成换热单元换热量（Qn）概率分布的影响，在此基础上采用换热单元换热量生成与分布概率协调的换热网络优化策略，摄动后小概率随机生成换热量较大的换热单元，同时改变Qn的概率分布情况，用于增强结构进化能力。最后采用15SP和20SP算例验证该策略的可行性，较文献结果分别降低了435 498和42 253 $/a，由此证明，该策略可有效提高算法的局部搜索精度和全局搜索能力。

When the random walk algorithm with compulsive evolution algorithm is applied to the optimization of heat exchange network,it has the characteristics of simple algorithm program and strong structural evolutionary capacity.But it is still difficult to find the evolutionary direction that can further reduce the annual comprehensive cost in the later stage of individual evolution of the population.In view of this,the effect of the maximum heat transfer (Qmax) on the optimization process and the probability distribution of the new unit heat exchange (Qn) are investigated.Wtihcoordination strategy of heat transfer and distribution probability of new unit heat exchange,large heat exchange unit is generated randomly with perturbation,and the probability distribution of Qn is altered to enhance the capacity of structural evolution.Finally,15 SP and 20SP examples are used to verify the feasibility of the strategy.And it is determined that they are 435 498 and 42 253 $/a lower than the results in the literature,respectively.It demonstrated that the proposed strategy can effectively improve the local search accuracy and global search ability of the algorithm.

TB663

国家自然科学基金（51176125；21978171）；上海市科委部分地方院校能力建设计划（16060502600）