Wireless Ad hoc Sensor Network (WASN) is an evolving communication technology that can manage its operations by sensing the dynamic wireless environment in the absence of any pre-established infrastructure. In this paper, a meta-heuristic optimal approach has been proposed to frame the energy consumption and throughput model of wireless ad hoc communication system based on multiple scenarios using a multi-objective evolutionary algorithm called Non-dominated Sorting based Genetic Algorithm (NSGA-II). Each state is represented by multi-objective fitness functions and presented as a composite function of one or more radio parameters. A dynamic heterogeneous mobile WASN system has been simulated to develop an optimal model for energy consumption and throughput based on NSGA-II for stable clustering and routing. Computation has been made on the fitness score by considering multiple outcomes at times and then, evolving the solutions until optimal value is reached. The final results are represented as a set of optimal solutions called Pareto-front. The multi-objective optimization has been performed in this paper by considering multiple objectives. The finest individual fitness values which are obtained as the optimal Pareto-front are compared with the results of existing protocol.
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