Wireless sensor networks (WSN)are utilized for measuring various parameters such as pressure, temperature or humidity monitoring, in buildings to monitor smoke and fire, surveillance monitoring and also for environmental monitoring etc. These sensors are comprised of numerous small electronic devices known as sensors which are operated on battery. The wireless sensors are deployed in the chosen region according to the area of interest so that it can continue sensing for a long duration. But to keep these sensors active for a desired duration, the network’s lifetime should be necessarily prolonged with less power consumption because unbalanced battery usage becomes a major challenge in WSNs. There has been a vast research in last few decades on different types of protocols depending upon the type of network i.e. homogenous or heterogeneous. It is seen that energy efficiency can be obtained by clustering methods.  Various meta-heuristic optimization techniques also have been proposed earlier to resolve the optimization problems. In this paper, we aim to achieve energy efficiency by using fuzzy logic for cluster formation and Grey Wolf Optimizer (GWO) for cluster head (CH) election.