Grey wolf optimizer (GWO) is a meta-heuristic algorithm adopted by grey wolf leadership theory and hunting swarm intelligence algorithm. Besides that, three basic hunting trials are used seeking prey encircling pray and attacking prey as a result, that GWO has attracted a large research involvement from a variety of areas in a less period. The existing GWO devotes half of its iteration to exploration and another half to exploitation ignoring the importance of finding the accurate balance among the two to ensure correct estimation of the optimum solution. To address this problem a 2D based optimization of gray wolf using the Firefly algorithm (GWO-FA) is introduced to overcome this problem and obtain to exact location. The GWO-FA algorithm and other meta-heuristics are used in this study to examine the 2D locations in an anisotropy atmosphere utilizing a different approach of placing the virtual anchors with parasol projection across the moving targeted nodes. In compared to certain known algorithms, simulations results show that this approach can deliver successful outcomes. The finding of the node localization challenge shows that the suggested approach is efficient in tracking actual situation involving uncertain solution space.