SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
SIAM Journal on Optimization
Superlinear Convergence and Implicit Filtering
SIAM Journal on Optimization
Global Optimization on Funneling Landscapes
Journal of Global Optimization
On the multilevel structure of global optimization problems
Computational Optimization and Applications
Global Optimization of Morse Clusters by Potential Energy Transformations
INFORMS Journal on Computing
Search space pruning and global optimisation of multiple gravity assist spacecraft trajectories
Journal of Global Optimization
A hybrid multiagent approach for global trajectory optimization
Journal of Global Optimization
Sequential Penalty Derivative-Free Methods for Nonlinear Constrained Optimization
SIAM Journal on Optimization
Machine learning for global optimization
Computational Optimization and Applications
Search for a grand tour of the jupiter galilean moons
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Space pruning monotonic search for the non-unique probe selection problem
International Journal of Bioinformatics Research and Applications
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The problem of optimally designing a trajectory for a space mission is considered in this paper. Actual mission design is a complex, multi-disciplinary and multi-objective activity with relevant economic implications. In this paper we will consider some simplified models proposed by the European Space Agency as test problems for global optimization (GTOP database). We show that many trajectory optimization problems can be quite efficiently solved by means of relatively simple global optimization techniques relying on standard methods for local optimization. We show in this paper that our approach has been able to find trajectories which in many cases outperform those already known. We also conjecture that this problem displays a "funnel structure" similar, in some sense, to that of molecular optimization problems.