Multidisciplinary design of air launched satellite launch vehicle: Performance comparison of heuristic optimization methods

Satellite launch vehicle design lies at the cross-road of multiple challenging technologies and its design and optimization presents a typical example of multidisciplinary design and optimization process. The complexity of problem demands for highly efficient and effective algorithm that can optimize the design. This research effort aims to evaluate and compare three modern heuristic optimization methods for multidisciplinary design and optimization of air launched satellite launch vehicle. Furthermore, sensitivity analysis of solutions presented the robustness of solution of these methods under parametric uncertainty. The Monte Carlo simulation method conducted the sensitivity analysis of the solutions. Heuristic optimization methods evaluated for current research include genetic algorithm, particle swarm optimization and simulated annealing. Genetic algorithm has been the most popular choice of designers for satellite launch vehicles. Application of other two methods in design and optimization of satellite launch vehicles is rare and thus become the motivational ingredient for the present research.