Modular process recombination method based on improved genetic algorithm

Abstract

The invention provides a modular process recombination method based on an improved genetic algorithm. According to the invention, a product demand value module process recombination set containing a plurality of process routes can be obtained through calculation. The method has creative breakthrough. The method comprises the following steps: randomly generating an initial population with a certainscale; and then combining an immune genetic algorithm and an elite retention strategy, and replacing the individual with the worst fitness in the randomly generated initial population with an elite antibody, so that the diversity of the initial population can be ensured, the number of later populations can be improved, and excellent individuals are replaced and guide the population to evolve in the genetic process to quickly approach a target value. By adopting the method to carry out modular process generation, a plurality of process recombination sets with high satisfaction can be obtained,the process decision time is shortened, and the productivity is improved.

Description

technical field [0001] The invention relates to the field of industrial big data analysis, in particular to a modular process reorganization method based on an improved genetic algorithm. Background technique [0002] The main realization method of mass customization is modular product configuration. Modular process recombination is to establish a model of process modules and combine them into a complete process through the mutual constraints between process modules and their attributes, so as to avoid invalid process combinations and improve the efficiency of product process matching. The matching method of modular processing conforms to the concept of mass customization. The process matching process is to meet the product demand as the starting point, and the matching result is closely related to the product attributes. On the other hand, through the existing historical processing technology and experience in the example library, and through the matching algorithm, the i...

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Problems solved by technology

[0004] The technical problem mainly solved by the present invention is that in the industrial big data environment, there is no set of fixed methods and steps to follow in the expert experience method, which is very tentative and arbitrary, and there is no general method for different products. Defects such as easy-to-grasp design methods, combined with the advantages of more accurate parameter setting and simple design steps, a modular process reorganization method based on improved genetic algorithm is proposed

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