Current design evaluation methods often suffer from issues such as subjectivity

uncertainty

and randomness. In response

this study proposes an innovative aesthetic evaluation approach that combines genetic algorithms with an enhanced CRITIC-GRA-TOPSIS integrated assessment. The method begins to optimize product family morphological features using a genetic algorithm

grounded in aesthetic computation principles. It then explores various aesthetic dimensions

establishes an index system for aesthetic evaluation

and quantifies aesthetic feature indicators through computational principles.To enhance objectivity

an improved CRITIC method is employed to determine weights for each criterion. The GRA-TOPSIS method is finally applied to calculate comprehensive evaluations and establish a rankingusing these criterion weights. Validated through experiments focusing on automotive headlights and compared with existing methods

this approach demonstrates its feasibility and applicability. The research results highlight the model's accuracy and objectivity in providing a quantitative assessment of product aesthetics

presenting a promising and effective alternative for aesthetic evaluation.