This paper proposes a rapid trajectory optimization approach using artificial neural network metamodel for two application areas i.e. firstly for incorporating trajectory optimization at the conceptual design level and secondly for guidance with onboard reoptimization of the trajectory in near real time. Particle Swarm Optimization is employed for conceptual design optimization, whereas, Sequential Quadratic Programming is used for onboard trajectory optimization. We first describe our methods for analyzing vehicle design and then we incorporate those methods into optimization problem, the solution of which yields minimized launch weight. In addition to optimal vehicle configuration, this study also optimizes ascent trajectory in an integrated manner. In second application area, closed loop guidance scheme uses trajectory metamodel based on neural network for online near real time trajectory optimization. Dispersion analysis of open loop guidance and proposed closed loop guidance are conducted and shows that proposed scheme makes the system more robust. Trajectory metamodel using neural network shows promising results for both guidance and conceptual design optimization applications.