Three-way decision method for project selection based on hesitant fuzzy sets and cumulative prospect theory

In large-scale planning project selection, sound decision-making directly affects resource allocation and implementation outcomes. Addressing prevalent challenges of fuzzy decision-making information and significant psychological behavioural factors among decision-makers (DMs), this paper proposes a three-way decision (3WD) method integrating hesitant fuzzy sets (HFS) and cumulative prospect theory (CPT) for project scheme selection. First, HFS characterises DMs’ evaluative hesitancy through membership degree sets, while CPT captures their risk preferences. Building on this foundation, four improved TOPSIS optimisation models based on hesitant fuzzy positive/negative ideal solutions are developed. These models classify alternatives into priority, boundary and rejection domains via sequential 3WD, enabling flexible categorisation and optimisation. Subsequently, an adaptive fusion mechanism grounded in hesitant fuzzy consistency measurement is introduced to consolidate multi-model ranking results, mitigating single-model bias. Case analysis in urban construction planning shows that the proposed method improves selection objectivity and provides a framework for decision-making under complex uncertainty.