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In this paper, we explore using a hybrid evolutionary algorithm (HEA) for deploying and configuring a set of given sensors on a synthetically generated 3-D terrain. In our evolutionary-algorithm (EA) based solution, various methods are considered in order to incorporate specialized operators for hybridization, including problem-specific heuristics for initial population generation, intelligent variation operators (contribution-based-crossover operator and proximity-based-crossover operator), which comprise problem-specific knowledge, and a local-search phase. The experimental study validates finding the optimal balance among visibility-oriented, stealth-oriented, and cost-oriented objectives. The obtained results also indicate the effectiveness and robustness of our HEA-based solution for various practical scenarios with different objectives.