A Multi-Objective Recipe Recommender System with Structural Safety Constraints for Allergen-Aware Diets

Food allergies impose strict constraints on dietary decision-making, necessitating recommender systems that guarantee safety without compromising nutritional quality or user satisfaction. Existing systems often treat safety as a preference, failing to meet rigorous safety-critical standards or account for complex interactions between allergens, nutrition, and visual appeal. To address this issue, we propose a structured, multi-objective recipe recommendation framework. In this framework, rather than being modeled as an additive objective, allergen safety is prioritized through a safety-aware penalty-based ranking mechanism. The framework integrates three core modules: an allergen safety score accounting for cross-reactivity and cooking conditions; a nutritional balance score aligned with Dietary Reference Intakes (DRIs); and a neural-derived visual appeal score. In evaluation, we conducted a controlled user study (N=20) to evaluate the framework against single-factor baselines. Our integrated strategy consistently outperforms all single-factor baselines across evaluated metrics. Sensitivity analysis further confirms that safety-aware ranking ensures stable recommendation behavior across diverse preference profiles. Notably, behavioral analysis revealed a decision–action discrepancy, wherein users exhibited more risk-averse behavior during actual interactions than their explicitly stated preferences suggested. These findings suggest that prioritizing safety through safety-aware ranking mechanisms, together with multi-objective optimization, provides a robust foundation for personalized health-aware dietary support.