关键词: 换热网络, 同步综合, 混合整数非线性规划, 粒子群算法, 遗传算法

Abstract: Heat exchanger network is an important energy recovery system in chemical processes. Recently, simultaneous synthesis methods have been frequently applied to designing a cost-optimal heat exchanger network.Simultaneous synthesis problem is usually formulated as a mixed-integer non-linear programming model, which is non-convex, nonlinearity, non-continuous, and belongs to one of the toughest non-deterministic polynomial-time hard（NP-hard)problems.Medium or large-scale simultaneous synthesis problems in many cases cannot be solved in a reasonable time.A two-level approach was proposed for solving HENS problem.A hybrid methodology consisting of binary particle swarm optimization and genetic algorithm was utilized to generate the network structure in the upper level, while in the lower level, the heat load of exchangers and split-stream fractions were optimized by an improved particle swarm optimization.Two benchmark problems were solved to prove the efficiency of the proposed method.

Key words: heat exchanger network, simultaneous synthesis, mixed-integer non-linear programming;particle swarm optimization, genetic algorithm