The Fellowship of the Dyson Ring: ACT&Friends' Results and Methods for GTOC 11

TL;DR

This paper presents a comprehensive, automated pipeline combining machine learning, optimization, and scheduling techniques to solve complex trajectory planning for constructing a Dyson ring, achieving second place in the GTOC 11 challenge.

Contribution

It introduces novel methods including a machine learning transfer time estimator, optimized low-thrust transfers, and an evolutionary scheduling algorithm integrated into a unified pipeline.

Findings

Achieved second place in GTOC 11 challenge.

Developed a machine learning transfer time estimator.

Created an integrated pipeline for trajectory planning.

Abstract

Dyson spheres are hypothetical megastructures encircling stars in order to harvest most of their energy output. During the 11th edition of the GTOC challenge, participants were tasked with a complex trajectory planning related to the construction of a precursor Dyson structure, a heliocentric ring made of twelve stations. To this purpose, we developed several new approaches that synthesize techniques from machine learning, combinatorial optimization, planning and scheduling, and evolutionary optimization effectively integrated into a fully automated pipeline. These include a machine learned transfer time estimator, improving the established Edelbaum approximation and thus better informing a Lazy Race Tree Search to identify and collect asteroids with high arrival mass for the stations; a series of optimally-phased low-thrust transfers to all stations computed by indirect optimization techniques, exploiting the synodic periodicity of the system; and a modified Hungarian scheduling algorithm, which utilizes evolutionary techniques to arrange a mass-balanced arrival schedule out of all transfer possibilities. We describe the steps of our pipeline in detail with a special focus on how our approaches mutually benefit from each other. Lastly, we outline and analyze the final solution of our team, ACT&Friends, which ranked second at the GTOC 11 challenge.