Heat pumps can enhance the utilization of low-grade thermal energy. Setting heat pumps correctly in a heat exchanger network can reduce the consumption of cold and hot utilities, achieving energy saving and pollution reduction. Therefore, targeting the optimal placement of heat pumps is of great interest in both the academia and industry. Focusing on the vapour compression heat pump, this work proposes a simulation-optimization method to identify the energy-optimal placement of heat pumps in heat exchanger networks. Based on the powerful fluid property database, the vapour compression heat pump system is first modelled in the Aspen HYSYS V10. Next, a mathematical model is built in the Matlab R2018b platform using the Grand Composite Curve of heat exchanger network as constraints for heat pump placement. The two platforms, Aspen HYSYS V10 and Matlab R2018b, are then coupled to realize the data transfer between the simulation and mathematical models. The genetic algorithm is used to target the energy-optimal placement of heat pump (evaporating temperature, condensing temperature, and working fluid flowrate) in the heat exchanger network. A case study is performed to illustrate the applicability of the proposed method. The proposed simulation-optimization method can be extended to other types of heat pumps.