Radiation dose is a concern in X-ray tomographic imaging; coded aperture compressive X-ray tomosynthesis is an approach used to reduce radiation. It places a coded aperture in front of an X-ray source in order to obtain 2D patterned projections of a three-dimensional object onto a detector plane. By using different coded apertures in a multiple source system, multiplexed projections can be obtained instead of sequential projections as in conventional tomosynthesis systems. Compressed sensing (CS) reconstruction algorithms are then used to recover the three-dimensional data cube. An optimization approach to design the structure of the coded apertures in a multiple source compressive X-ray tomosynthesis imaging system is presented. A uniform energy criteria on the voxels and detector elements is used so that the object is uniformly sensed and the elements of the detector plane uniformly sense the information. Simulations and experimental results for optimized coded apertures are shown, and their performance is compared to the use of random coded apertures.