Ad hoc networks are made up of a collection of wireless mobile nodes that form a temporary network with no pre-existing infrastructure or centralized management.Routing policies are crucial in determining how traffic is forwarded across a network. Adhoc networks necessitate a routing method that is very adaptable. Finding the shortest path (SP) between source and destination in a specific period of time to meet Quality of Service standards is one of the most common issues in these networks (QoS). QoS routing is difficult in an Ad hoc network because the topology changes frequently and it takes time since many QoS criteria such as distance, cost, and energy are all variable, and the state information supplied for routing is inherently faulty. The optimum path for Adhoc networks is found using a Genetic Algorithm (GA) in this paper.GA uses natural evolution-inspired methodologies to find answers to optimization problems. Crossover and mutation operations, as well as the proper chromosome structure, are all defined.
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