This document contains a report on the work done under the ESA/Ariadna study 06/4101 on the global optimization of space trajectories with multiple gravity assist (GA) and deep space manoeuvres (DSM). The study was performed by a joint team of scientists from the University of Reading and the University of Glasgow

Anderson, James D.

Becerra, Victor M.

Ceriotti, Matteo

Nasuto, Slawomir J.

Radice, Gianmarco

Vasile, Massimiliano

University of Strathclyde Institutional Repository

English

Advanced global optimisation for mission analysis and design. Final report. ariadna id: 03/4101. contract number: 18138/04/nl/mv, European Space Agency,

Constraint handling techniques for a non-parametric real-valued estimation distribution algorithm.

Dierential Evolution|a simple and ecient heuristic for global optimization over continuous spaces.

Differential Evolution—a simple and efficient heuristic for global optimization over continuous spaces.

Matlab implementation of the Mean Shift Clustering algorithm.

Mean sh a robust approach toward feature space analysis.

Mean shfit: a robust approach toward feature space analysis.

Particle swarm optimization for integer programming.

Particle swarm optimization.

Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories.

Search space pruning and global optimization of multiple gravity assist trajectories with deep space manoeuvres.

Global Trajectory Optimisation : Can We Prune the Solution Space When Considering Deep Space Manoeuvres? [Final Report]