Bio-inspired computing for launch vehicle design and trajectory optimization

This paper presents an optimization tool for launch vehicle design and trajectory optimization using bio-inspired computing algorithms and nonlinear programming. The objective is to size a launch vehicle such that the payload to lift-of-weight ratio is maximized (i.e the lift off weight is a minimum). Here, the staging problem is solved using Particle Swarm Optimization (PSO) method. With the above vehicle, an optimal trajectory is arrived at using a Real-Coded Genetic Algorithm (RCGA) and solving a nonlinear programming (NLP) by the direct shooting method. The solutions from PSO and RCGA are used for initialization of NLP variables. A case study is carried out that establishes the advantage of the proposed approach.