Complex product full-process optimization design method based on incidence matrix tree hierarchical evolution

Abstract

The invention discloses a complex product full-process optimization design method based on incidence matrix tree hierarchical evolution. The method includes: performing multi-granularity decomposition on the production line to form a preliminary incidence matrix tree; setting and calculating the importance and incidence strength of elements in the association matrix tree; and performing inter-level mapping on the incidence matrix tree, solving coarse-grained incidence strength among elements through level evolution, and constructing a target incidence matrix by using the coarse-grained correlation strength to finish establishment of the whole incidence matrix tree finally. According to the method, unified expression of incidence relationships of different granularity composition elements of the system is realized, and the problem that quantitative conversion from incidence strength to importance is difficult is solved; accurate mapping between layers of the incidence matrix tree is achieved, and accurate expression of the incidence relation of production line equipment is guaranteed.

Description

technical field [0001] The invention belongs to a production process reconstruction optimization method in the field of complex products, and in particular relates to a complex product whole-process optimization design method based on the hierarchical evolution of an association matrix tree. Background technique [0002] An incidence matrix is ​​a system modeling tool used to describe the flow of information. The correlation matrix tree has good visualization, strong ability to express information, and various algorithm systems are mature. It has become an important modeling tool for research and analysis of complex systems worldwide. The matrix obtained by the traditional correlation matrix tree construction method is generally discrete, and the modeler directly gives the correlation strength between elements according to experience, or gives several types of correlation strength from different inspection angles, and then gives the final weighted method. The correlation st...

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Problems solved by technology

The matrix obtained by the traditional correlation matrix tree construction method is generally discrete, and the modeler directly gives the correlation strength between elements according to experience, or gives several types of correlation strength from different inspection angles, and then gives the final weighted method. The correlation strength is no

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