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.