Heat exchanger network synthesis can be described by a mixed integer non-linear programming(MINLP) model

which features non-convex

non-linear and non-differentiable optimization. The parallel computing technology based on GPU provides an efficient support for solving large scale models. In this work

a hybrid algorithm combined branch and bound method(BB) with sequential quadratic programming(SQP) is proposed to overcome difficulties in the existing parallel SQP algorithm

such as too many combinations of integer variables

dependency of initial values and etc.. The BB method is adopted in the hybrid algorithm instead of the exhaustive method. It can not only reduce the combinations of integer variables

but also select feasible initial values for the SQP algorithm. The solution quality is improved. The results of the examples show that the proposed parallel hybrid algorithm can solve the heat exchanger network synthesis problems efficiently. Compared to the serial algorithm

the proposed parallel algorithm has much higher executive speed with the speedup ratio of 39.