Traditional low-power adaptive hierarchical cluster protocols in wireless sensor networks have high node energy consumption, short network lifetime, and unbalanced load. In order to solve these problems, this study proposes a Harris hawks routing optimization algorithm that reflects multi-objective cluster head election and is based on simulated annealing in heterogeneous sensor networks. On the basis of calculating the optimal threshold of nodes, the improved algorithm firstly constructs a new fitness function considering energy consumption and load to find the optimal cluster head node and ensure the uniform distribution of cluster head nodes. Then, a path selection strategy based on Harris hawks optimizer is established, and the simulated annealing algorithm is embedded to prevent from premature local optimum. Finally, the study uses an evaluation function to select cluster heads that can be added to the optimal path to shorten the communication distance between cluster head nodes and base stations. The simulation results show that compared with the CREEP, LEACH-C, and LEACH algorithms, the proposed algorithm prolong the network lifetime by 22.18%, 77.83%, and 180.52%, respectively, and thus they can prolong the network lifetime more effectively.