GTOC 12: Results from TheAntipodes

TL;DR

This paper details the solution approach by TheAntipodes team for GTOC 12, combining heuristic asteroid subset generation, beam search chain building, convex low-thrust trajectory optimization, manual refinement, and genetic algorithms to achieve a high-scoring mission plan.

Contribution

The paper introduces a comprehensive multi-step method integrating heuristics, convex optimization, manual tuning, and evolutionary algorithms for complex asteroid mission planning.

Findings

Final solution ranked fifth with a score of 15,489.

The approach effectively combines multiple optimization techniques.

Convex low-thrust trajectory optimization runs in seconds.

Abstract

We present the solution approach developed by the team `TheAntipodes' during the 12th edition of the Global Trajectory Optimization Competition (GTOC 12). An overview of the approach is as follows: (1) generate asteroid subsets, (2) chain building with beam search, (3) convex low-thrust trajectory optimization, (4) manual refinement of rendezvous times, and (5) optimal solution set selection. The generation of asteroid subsets involves a heuristic process to find sets of asteroids that are likely to permit high-scoring asteroid chains. Asteroid sequences `chains' are built within each subset through a beam search based on Lambert transfers. Low-thrust trajectory optimization involves the use of sequential convex programming (SCP), where a specialized formulation finds the mass-optimal control for each ship's trajectory within seconds. Once a feasible trajectory has been found, the rendezvous times are manually refined with the aid of the control profile from the optimal solution. Each ship's individual solution is then placed into a pool where the feasible set that maximizes the final score is extracted using a genetic algorithm. Our final submitted solution placed fifth with a score of $15,489$.