换热网络中温度交叉结构的分析与处理

在以换热量作为待优化连续变量的换热网络优化问题中，流股匹配可能出现温度交叉，常以惩罚函数法处理存在温度交叉的不可行结构.然而，当采用强制进化随机游走算法时，由于其接受差解的变异操作，温度交叉结构可能以差解的形式被接受，对优化进程产生负面影响而降低优化效率.因此，首先分析换热网络中温度交叉结构的成因，接着分析该不可行结构对算法优化进程的消极作用，然后提出一种处理方法，当种群中个体随机游走到不可行域时，强制使其回到可行域内的原位重新优化，从而提升算法优化效率.

Analysis and Treatment on Structures with Temperature Cross in Heat Exchanger Network

As heat exchange loads are treated as continuous variables to be optimized in heat exchanger network (HEN) problems, temperature cross could be generated in stream matches. Infeasible structures with temperature cross are penalized by penalty function method in literature. However, in random walk algorithm with compulsive evolution (RWCE) algorithm to HEN optimization, structures with temperature cross may be accepted as imperfect solutions due to its mutation operation of accepting imperfect solutions, which may negatively affect optimization process and decrease algorithm efficiency. Hence, temperature cross in HEN is firstly explained. Then negative effects of infeasible structures on optimization process of RWCE is described. A treatment method is proposed: Individuals trapped in infeasible regions are compulsively returned to their original positions in feasible regions to accept re-optimization. It was demonstrated that the proposed method improves algorithm efficiency and achieves better results than reported ones in literature.