Abstract: Optimizing material storage for composite material layup in aerospace blade manufacturing, a novel hybrid algorithm integrating a knapsack problem and dynamic programming is proposed. The algorithm establishes a dual-objective evaluation model for material value and spatial efficiency, constructing a multi-objective optimization function constrained by storage layer count, area, and utilization rate. A dynamic programming approach combined with backtracking pruning strategies is employed to optimize the hierarchical layout of material sheets. Experimental validation using a typical case with 17 material types demonstrates the algorithm’s efficacy. In multi-layer optimization scenarios, the average spatial utilization rate improved from 79.36% to 99.89%, representing a 25.9% enhancement over traditional methods. Additionally, the interlayer matching of the silo space is dynamically adjusted, the total space is reduced by 20.5%. The results confirm that the algorithm effectively balances spatial efficiency and process value through dynamic parameter optimization, offering a high-performance storage solution for complex component manufacturing.

Key words: material storage optimization, dynamic programming, knapsack problem, combinatorial optimization, composites