GTOC X: Solution Approach of Team Sapienza-PoliTo

TL;DR

This paper presents a novel solution approach for the 10th Global Trajectory Optimization Competition, involving a partitioned galaxy model, a multi-settler stochastic search, and star transfer optimization, achieving solutions with 1013 and 1200 stars.

Contribution

It introduces a new multi-settler stochastic Beam Best-First Search method combined with a partitioning strategy for galaxy coverage optimization.

Findings

Achieved a 1013-star solution for the competition.

Developed an enhanced 1200-star rework.

Implemented effective star transfer and settlement optimization techniques.

Abstract

This paper summarizes the solution approach and the numerical methods developed by the joint team Sapienza University of Rome and Politecnico di Torino (Team Sapienza-PoliTo) in the context of the 10th Global Trajectory Optimization Competition. The proposed method is based on a preliminary partition of the galaxy into several small zones of interest, where partial settlement trees are developed, in order to match a (theoretical) optimal star distribution. A multi-settler stochastic Beam Best-First Search, that exploits a guided multi-star multi-vessel transition logic, is proposed for solving a coverage problem, where the number of stars to capture and their distribution within a zone is assigned. The star-to-star transfers were then optimized through an indirect procedure. A number of refinements, involving settle time re-optimization, explosion, and pruning, were also investigated. The submitted 1013-star solution, as well as an enhanced 1200-point rework, are presented.