Particle Swarm Optimization and Analytic Hierarchy Process for Functional Space Adaptation in Aging-in-Place Home Modifications: A Multi-Criteria Decision-Support Model for Accessibility and Independent Living in Elderly Housing

Abstract

Older adults commonly face challenges such as insufficient spatial accessibility and a lack of safety facilities in their home environments. This paper proposes a multi-criteria decision-making (MCDM) model integrating the Analytic Hierarchy Process (AHP) and Particle Swarm Optimization (PSO) to enhance the scientific rigor and practicality of age-friendly renovation solutions. Based on 543 valid questionnaires and interview data, an evaluation system was constructed, covering four key dimensions: safety assurance, spatial accessibility, independent living capability, and environmental comfort. The weight allocation incorporates dual-source fusion of expert judgment and sample-aggregated resident preferences to improve model rationality and stability. Results demonstrate that the AHP-PSO model outperforms comparative models in prediction accuracy (MAE = 0.121), functional reasonableness (FDR = 0.136), dimensional balance (DBR = 0.912), and robustness (FSR = 94.8%). Comprehensive adaptation analysis reveals that while most residences satisfactorily meet the needs of the elderly, emergency response facilities, kitchen convenience, and furniture adaptability remain critical shortcomings constraining overall performance. The findings validate the effectiveness of the AHP-PSO model for age-friendly home modifications, providing methodological support for resource allocation optimization and aging-in-place policy formulation.