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Wireless Ad Hoc Networks are capable of communication through wireless medium without the need for a pre-existing infrastructure. Much effort has gone into mobile ad-hoc network (MANET) research over the past decade. Yet, even today, mobile ad-hoc networking is seen as a relatively new area of research. The reason for this can be traced to the fact that the maturity in truly understanding these networks is still alarmingly low and actual deployment of these networks rare. There are plenty of techniques in route finding and link establishment in MANET based on various concepts such as “pro-active”, “reactive”, “power awareness”, “cross-layering” etc. Most of these techniques are rather restrictive, taking into account a few of the several aspects that go into effective route establishment. The several factors that decide and influence the routing have to be considered as a whole in the difficult task of finding the best solution in route finding and optimization. The inputs to the system are manifold and apparently unrelated. Most of the parameters are imprecise or non-crisp in nature. The uncertainty and imprecision lead to think that intelligent routing techniques are essential and important in evolving robust and dependable solutions to route finding. The obvious method by which this can be achieved is the deployment of soft computing techniques such as Neural Nets, Fuzzy Logic and Genetic algorithms. Our paper presented here seeks to explore new horizons in this direction. The results of our experimentation with simulator named hypernet have been very satisfactory and we have achieved the goal of optimal route finding to a large extent.