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In this paper, Multiobjective Mobile Antenna Location identification problem is considered with site coordinates (x, y), transmitting power, height, and tilt angle as design parameters and maximization of service coverage and minimization of cost as objectives. Evolutionary multiobjective algorithm NSGA-II and modified NSGA-II by incorporating dynamic crowding distance and controlled elitism is considered. A 15×15 Km2 synthetic test system is taken for simulation purposes. From the simulation results, we realize that modified NSGA-II is able to generate better Paretofront in terms of diversity and uniformity.