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Recent advances in sensors technology have led to design and development of variety of geosensor networks and their applications in many disciplines. Such networks consist of a set of sensors laying on different locations and sensing various real world phenomena for environmental monitoring, object surveillance, tracking and controlling applications. A fundamental issue in a geosensor network optimization is estimation of its spatial coverage. The existence of various obstacles in the sensing environment and its complexity result in several holes in the environment. These holes should be detected and minimized in the optimization process. Different approaches have been proposed in the literatures to resolve these problems. A considerable number of current approaches use Voronoi diagram and Delaunay triangulation to identify the holes in the network and deploy an optimal arrangement for the sensors. These structures are more compatible with the spatial distribution of sensors in the environment. This paper presents a survey of the existing solutions for geosensor network optimization that use Voronoi diagram and Delaunay triangulation in their approach.