Optimization of space debris removal sequence using dynamic programming with hazard index consideration

This paper presents an optimization framework for active space debris removal missions using dynamic programming with hazard index consideration. The object selection problem is formulated as a modified knapsack problem. For low-thrust trajectory fuel consumption estimation, a standard maneuvering cycle is considered, analyzed using Edelbaum's solution. The hazard index is evaluated based on the proximity of space debris objects to a protected orbital region. The proposed approach enables efficient candidate selection for future debris removal missions. The developed algorithm demonstrates high performance when processing groups of several hundred candidates, allowing the selection of 5-20 high-risk objects for annual removal. Simulation results for geostationary (GEO) and low Earth orbits (LEO) determine the optimal trade-off between ∆V costs and mission duration. The method provides a foundation for autonomous decision systems in orbital debris mitigation campaigns. © © 2025 The Authors.