Abstract:

To solve the problem of the lack of optimization tools in the matrix-based solving process of the functional chain design solution, an optimization method based on computational matrix combined with ant colony algorithm is proposed. The similarity theory is analyzed, and similarity and generalized distance are used to characterize the compatibility of the two adjacent elements. The similarity matrix is defined, and the design solution matrix containing similarity information is acquired by the calculation of the similarity matrix and the design solution matrix. The design scheme evaluation model and the ant colony algorithm based optimization model are defined, and the calculation method of the evaluation criterion, weight and value is proposed. As the evaluation score of components is pheromone and as the length of generalized distance is the path of adjacent nodes, the pheromone matrix and probability matrix is structured. The problem of solution solving is converted to the optimal path problem of combinatorial optimization. The design solution contained in the design solution matrix is optimized with ant colony algorithm, and the optimized design solution meeting the functional requirements, structural requirements and the evaluation target is obtained. Finally, the effectiveness of the proposed method is verified with an example of three-axis servo drive.

Key words: ant colony algorithm, computational matrix, design solution solving, similarity theory, conceptual design