Heat Exchanger Network (HENET): A parallel GA/SA algorithm

Heat exchanger network (HEN) synthesis has been a well-studied subject over the latest decades. Many studies and methodologies were proposed to make possible the energy recovery. Based on simulated annealing and genetic algorithm, this paper presents an efficient simultaneous synthesis method that provides the optimal networks in a twolevel procedure. Genetic algorithm is used by an evolutionary algorithm to manage HEN topology and simulated annealing is used to manage heat load distribution among exchangers. This two-level method is applied to solve one benchmark that includes 28 instances with different dimensions, from 3 to 39 streams. For every instance, this benchmark includes the best result obtained with a state-of-the-art algorithm from the literature, which has been useful in this work to compare our proposed hybrid algorithm with the best existing approaches. The results of this study show that, in some situations, the hybrid approach is able to derive networks that are more economical than those from the known solutions in the literature.