Intelligent search strategy applied in heat exchanger network synthesis

Abstract

Heat exchanger network (HEN) synthesis has been acknowledged as an effective design technique to achieve significant energy savings in a wide range of industrial and engineering applications. In this regard, heuristic methods have been demonstrated as a powerful means to solve the HEN synthesis problem. However, because the new structure is generated at random, the structures that can effectively make the objective cost descend are limited in comparison to the entire evolutionary process. In addition, such heuristic methods are usually time-consuming processes. In this work, an intelligent search strategy is proposed to increase the efficiency of heuristic methods. Based on the defined objective cost, this strategy could rapidly and effectively find a route that could satisfy cost minimization. It can also achieve further evolution aimed at highlighting potential structures. The proposed search strategy can increase the ability of searching and reduce time consumption. Considering the random walk algorithm with compulsive evolution as an example, the principle and impact of intelligent search were clearly demonstrated. Furthermore, applying the intelligent search strategy to the random walk algorithm with compulsive evolution to some cases in the existing literature was found to yield better solutions.