 This paper proposes a novel hybrid cat cheetah optimization algorithm, HC-20A, for energy efficient clustering based rooting in underwater wireless sensor networks, UWSNs. The network is divided into multiple clusters, each of which is led by a cluster head, CH, and comprises of several sub-clusters, SCS. The CH selection is optimized using the factors such as distance and residual energy, while the multi-hop transmission approach is used to transmit collected data from the SCS to the SYNC nodes, SNs. This optimizes the energy efficiency of the network and reduces the complexity of multi-hop rooting. Simulation results demonstrate that the proposed workout performs existing approaches in terms of network lifetime, packet delivery ratio, and energy consumption. This article was offered by MMVJ, J. Sunil, V. G. Anishinana, Vinci, and others.