Systematic fuzzy decision-making reveals optimal asteroid candidates, suggesting robust methodologies for mission planning.
A systematic fuzzy multi-criteria decision making (MCDM) framework is proposed to prioritize near-Earth asteroids (NEAs) for a boulder capture mission, addressing the requirement for rigorous prioritization of asteroid candidates under conditions of data uncertainty. Twenty-eight NEA candidates were first selected through filtering based on physical and orbital properties. Then, objective fuzzy weighting MCDM methods (statistical variance, CRITIC, and MEREC) were applied to determine the importance of criteria such as capture cost, synodic period, rotation rate, orbit determination accuracy, and similarity to other candidates. Subsequent fuzzy ranking MCDM techniques (WASPAS, TOPSIS, MARCOS) generated nine prioritization schemes whose coherence was assessed via correlation analysis. An innovative sensitivity analysis employing Dirichlet-distributed random sampling around reference weights quantified ranking robustness. All methodologies combinations consistently identified the same top four asteroids, with 2013 NJ ranked first in every scenario, and stability metrics confirmed resilience to plausible weight variations. The modular MCDM methodology proposed provides mission planners with a reliable, adaptable decision support tool for asteroid selection, demonstrably narrowing broad candidate pools to robust targets while accommodating future data updates.
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Ramírez et al. (2025) studied this question.
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