Introducing CCOA (Clothing Context-Aware Optimization Algorithm): A Novel Metaheuristic Approach for Context-Aware Multi-Objective Optimization

With the growing demand for personalized clothing, how to efficiently and accurately select the right clothing combination according to different occasions, weather conditions and personal preferences has become an urgent problem to be solved. This paper proposes a novel optimization method, namely the Clothing Context-Aware Optimization Algorithm (CCOA). The algorithm combines meta-heuristic optimization technology with human intuition in the matching process, comprehensively considers multiple factors such as weather, occasions, personal preferences, and realizes personalized and efficient clothing matching recommendations. Experimental verification shows that the algorithm has good performance in multi-objective optimization, meets the needs of real-world situations, and provides users with comfortable and beautiful matching solutions. It is worth noting that CCOA is not limited to the field of clothing matching. It also has a wide range of applicability and can be extended to other multi-objective decision-making optimization tasks, such as restaurant matching and travel luggage selection.