A monogenetic algorithm for optimal design of large-scale heat exchanger networks

The optimal design of large-scale heat exchanger networks is a quite difficult task not only due to its non-linear characteristics but also due to a great number of local optima in its solution space. An explicit analytical solution of stream temperatures for the superstructure heat exchanger networks was developed, which reduces number of decision variables significantly. Based on this solution, a mathematical model for synthesis of heat exchanger networks was formulated for searching the optimal configuration of a heat recovery system by a hybrid genetic algorithm. For large-scale heat exchanger networks, a monogenetic algorithm based on the optimization of sub-networks is proposed. In the first step of the optimization, the hybrid genetic algorithm is applied to the synthesis of the whole heat exchanger network for finding the functional groups (sub-networks) rather than the chromosomes (positions of the heat exchangers and splits of the streams) and genes (areas and heat capacity flow rates). Then the monogenetic algorithm for evolution of the functional groups is carried out to improve the HEN. This procedure was applied to examples taken from literature and better results were obtained.