IoT-assisted WSN contains various nodes, which are placed in huge scale that increases complications. Thus, challenges and issues of these networks fluctuate as compared to WSN. Hence, sensor nodes are imperative unit that runs on less energy resources. Hence, devising a robust and energy-effective protocol for increasing network lifetime is complex task. This paper devises a novel hybrid optimization driven approach for selecting cluster head (CH) in IoT-assisted WSN. Initially, simulation of IoT nodes is done by configuration. Thereafter, the Cluster Head selection is done using newly devised optimization technique, namely Taylor-Political optimizer (Taylor-PO). Thus, the fitness is newly developed by adapting certain attribute like energy, delay, inter and intra cluster distance, Link Lifetime (LLT), predicted energy and delay. Here, the multipath routing is accomplished using Tunicate Swarm grey wolf optimization (TSGWO). Thus, the proposed Taylor-PO is offered for effective Cluster Head selection along with multipath routing using TSGWO. The proposed Taylor-PO offered improved performance with smallest delay of 0.006sec, highest energy of 2.368J, highest throughput of 494.043kbps.