Analysis and Evaluation of Global Optimisation Algorithms for Gravity Assist Sequencing of Low Thrust Missions

Abstract

In this thesis work "Analysis and Evaluation of Global Optimization Algorithms for Gravity-Assist sequencing of Low-Thrust missions" research is conducted to verify if the optimization algorithms can �nd near optimal trajectories for low-thrust gravity-assist trajectory optimization problem. In most of the low-thrust gravity-assist trajectory optimization, the gravity-assist sequence is fed to the optimizer by a mission analyst. The aim of this thesis is to analyse optimization algorithms after including the gravity assist partner as part of the optimization, i.e optimizer itself chooses the gravity-assist sequence. A couple of global optimization algorithms, Random Search and Simulated Annealing are realized in object oriented language(C++) and several experimental results are evaluated to understand the behaviour of these algorithms on a system which is trying to optimize the low-thrust gravity-assist trajectories. Suitability of the optimization algorithm which is to be used in an optimization tool, is veri�ed.