Multi-disciplinary Design Optimization (MDO) has been the research interest for industries and academia for more than two decades. Optimization concepts in general are applied to individual disciplines with high fidelity information but when it c omes to multi-disciplinary problems it is represented by low fidelity codes or empirical relations due to the cost of computation involved. In this proposal a glide vehicle configuration design is posed as an MDO problem with high fidelity data to achieve the optimum design subjected to constraints. The problem is contradicting multi-objective and multi-disciplinary nature. The design is considered with aerodynamics, structures and trajectory disciplines. Aerodynamics & structures disciplines are represented by high fidelity surrogate models generated using Reynolds Averaged Navier Stokes (RANS) and Finite Element Method (FEM) respectively. This MDO framework uses Bi-level optimization concept called Collaborative Optimization for systems and subsystems (disciplines).