<p>This paper proposes a hybrid topology optimization method for the design of all-solid-state battery (ASSB) composite electrodes to enhance their electrochemical performance. While previous studies have derived optimal configurations using continuous design variables, these idealized results often feature infinitely fine material gradients that are practically impossible to fabricate. Powder metallurgy (PM) enables the fabrication of complex electrodes by arranging discrete granules with tailored compositions. However, it requires a design approach that strictly accounts for the discrete arrangement of granules. In this paper, the optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem to simultaneously determine the spatial arrangement of discrete granules and their internal continuous material compositions, thereby ensuring PM manufacturability. To bridge this gap between theoretical design and practical fabrication, we propose a two-stage iterative algorithm. This approach employs a discrete optimization phase using Simulated Annealing (SA) to arrange the granules, followed by a continuous optimization phase using a gradient-based method to refine the volume fractions of active materials, solid electrolytes, and conductive additives within each granule. Numerical results demonstrate that the proposed method successfully reproduces the material configurations identified in the idealized model using continuous design variables while strictly satisfying discrete manufacturing constraints. The optimized structures reveal a spontaneously formed interdigitated configuration that balances the conflicting requirements of maximizing reaction interface area and securing continuous transport pathways for electrons and ions. This method provides a practical design tool for the development of high-performance ASSB electrodes, bridging the gap between theoretical topology optimization and realizable manufacturing processes.</p>