This study proposes a Hybrid Meta-Heuristic Evolution (HMHE) methodology to address the inherent trade-offs between material efficiency and production flexibility in 3D layout design. The method is designed to optimize towards both objectives concurrently: minimizing nesting sheet longitudinal width while preserving component variety, and optimizing sheet utilization under fixed width and height constraints. To accomplish this, the methodology utilizes Principal Component Analysis (PCA) for geometric feature extraction, which effectively reduces volumetric nesting complexity into optimized 2D build orientations while accounting for geometric constraints such as contour non-overlap and edge clearance requirements. The core innovation of this approach lies in a two-stage evolutionary workflow. The first stage introduces neighborhood transformations that generate localized solutions through rotational adjustments, contour permutations, and adaptive spacing strategies. The second stage applies a global optimization process driven by search agents and solution cross-pollination to explore a more diverse solution space. Technical implementations include advanced techniques such as contour simplification, matrix-based collision detection, and displacement-vector adaptations to resolve overlaps with precision. Experimental validation using human teeth within dental prosthetic layered manufacturing demonstrates the effectiveness of the HMHE method, achieving a 12.82% reduction in the sheet longitudinal width and a 12.19% improvement in sheet utilization. The proposed HMHE method introduces a hybridized optimization paradigm that enables dynamic prioritization of manufacturing objectives, offering a comprehensive and robust solution to improve production efficiency for resource-constrained environments where considerations of geometric feasibility and sustainability are critical.