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In this paper, we utilized a multi-objective approach to balance energy consumption and performance in wireless sensor networks (WSNs) that use a maximum likelihood estimation (MLE) approach for energy-based target localization. First, we developed measures that allow energy consumption and performance to be balanced in one-dimensional sensor arrays. Next, we extended these methods for two-dimensional arrays, employing approximations that facilitate computation of the energy consumption. Simulations were run to generate the Pareto-optimal fronts for both one-dimensional and two-dimensional sensor arrays. The Pareto-optimal fronts are useful in determining optimum points in practice.