In order to extend the lifetime of wireless sensor networks (WSNs) and their scalability, various methods have been proposed to solve this problem; one of the more effective methods is clustering. Clustering is an effective way to deal with topological problems, and it can be equally applied to the optimization of wireless wire sensor networks with network topology, where the choice of number and location of cluster heads in WSNs also has a significant impact on their lifetime as well as on various aspects of performance. In this chapter, the Phasmatodea population evolution algorithm is used for the selection of the number and location of cluster head nodes in WSNs to select the number and location of cluster heads that maximize the energy efficiency of the WSN network. It is shown experimentally that the proposed Phasmatodea population evolution algorithm–based optimization of WSN achieves good results.