The design of new Satellite Launch Vehicle (SLV) is of interest, especially when a combination of Solid and Liquid Propulsion is included. Proposed is a conceptual design and optimization technique for multistage Low Earth Orbit (LEO) bound SLV comprising of solid and liquid stages with the use of Genetic Algorithm (GA) as global optimizer. Convergence of GA is improved by introducing initial population based on the Design of Experiments (DOE) Technique. Latin Hypercube Sampling (LHS)-DOE is used for its good space filling properties. LHS is a stratified random procedure that provides an efficient way of sampling variables from their multivariate distributions. In SLV design minimum Gross Lift off Weight (GLOW) concept is traditionally being sought. Since the development costs tend to vary as a function of GLOW, this minimum GLOW is considered as a minimum development cost concept. The design approach is meaningful to initial design sizing purpose for its computational efficiency gives a quick insight into the vehicle performance prior to detailed design. The design of new Satellite Launch Vehicle (SLV) is of interest, especially when a combination of Solid and Liquid Propulsion is included. Proposed is a conceptual design and optimization technique for multistage Low Earth Orbit (LEO) bound SLV comprising of solid and liquid stages with the use of Genetic Algorithm (GA) as global optimizer. Convergence of GA is improved by introducing initial population based on the Design of Experiments (DOE) Technique. Latin Hypercube Sampling (LHS) -DOE is used for its good space filling properties. LHS is a stratified random procedure that provides an efficient way of sampling variables from their multivariate distributions. This SLV design minimum Gross Lift off Weight (GLOW) concept is traditionally being sought. Since the development costs tend to vary as a function of GLOW, this minimum GLOW is considered as a minimum development cost concept. The design approach is meaningful to initial design sizing purpose for its computational efficiency gives a quick insight into the vehicle performance prior to detailed design.