RWCE算法中选择性接受差解策略优化换热网络

强制进化随机游走算法优化换热网络时，以一定的概率接受差解可有效促进结构进化，非贪婪性的差解搜索机制是目标函数跳出局部极值的关键。本文分析接受差解机制的作用，探究不同优化阶段的差解结构来源，观察年综合费用变化，发现大多数被接受的差解结构在后续的优化中又回归到原结构，存在较多无效的参数传递过程。我们提出选择性接受差解策略，只接受具有新个体产生的差解，基于指数函数建立接受差解概率递增公式，并对结构中的新个体加以保护以增强其在结构中的存活率。最后选用9SP₂、20SP算例进行验证，取得了优于已发表文献的最优结果，证明了该策略的可行性。

An RWCE Algorithm for Heat Exchanger Network Optimization with Selective Acceptance of Imperfect Networks Strategy

As random walk algorithm with compulsive evolution is used to optimize heat exchanger networks, it promotes effectively structural evolution by accepting difference solution with certain probability. Non-greedy difference solution search mechanism is the key for the target function to jump out of local extremum. We analyze accept imperfect networks mechanism, explore different sources of imperfect networks of the optimization phase structure, and show the next year comprehensive cost change. We found that most acceptable solution return to the original structure in the subsequent optimization. There exist a lot of invalid parameter passing process. In this paper we present a selective acceptance of imperfect networks strategy, in which only difference solutions with new individuals are accpted based on an exponential increasing probability formula. Structure of new individual is protected to enhance its survival rate in structure. Finally, 9SP₂ and 20SP examples were used for verification. The optimal results are better than those in literature, which shows feasibility of the strategy.