The rise of 3D printing technology has stimulated a lot of hot research points in a number of research fields. The project Optimal Design in 3D Printing Applications has systematically studied many related topics in geometry processing, including saving printing material and printing time by structural optimization of 3D geometric models, feature-preserving denoising and construction of surfaces, and sequential construction and spurious sheets removal of 3D models. Many of the problems involve optimization models with complicated constraints, sparse representation and compress sensing. In this paper, we briefly summary the methods used in these problems, and reinterpret the use of operations research theories and algorithms in the perspective of geometric optimization, which indicates the importance and effectiveness of operations research tools in the study of related fields.