Personalized customization method based on improved interactive artificial immune algorithm

Abstract

The invention discloses a personalized customization method based on an improved interactive artificial immune algorithm. The personalized customization method comprises the following steps: S1, defining a personalized customization characteristic parameter system of a product; S2, obtaining a customer intention questionnaire, and constructing an intention weight matrix; S3, optimizing the initialantibody; S4, calculating the affinity between each antigen and the antibody; S5, updating the memory cells; S6, judging whether an optimal solution exists in the updated memory cells or not. Aimingat the existing problems of long iteration time, easy falling into a fatigue state of a client and the like in personalized customization, four processes of initial antibody generation, affinity calculation, crossover and mutation operators and optimal solution judgment in an artificial immune algorithm are improved, the convergence rate of the algorithm is effectively improved, and the time costis saved.

Description

technical field [0001] The invention relates to the field of personalized customization, in particular to a personalized customization method based on an improved interactive artificial immune algorithm. Background technique [0002] With the strategic goals of "German Industry 4.0", "American Industrial Internet" and "Made in China 2025", the transformation from traditional manufacturing to intelligent manufacturing is being promoted. The core of intelligent manufacturing is to meet the large-scale personalized customization. Whether it can accurately grasp and quickly respond to the diverse needs of consumers will become a key factor in improving the market competitiveness of enterprises. Therefore, customer-oriented customized production has become the mainstream production mode in the post-industrial era. [0003] The most important thing in product customization is to accurately obtain customer needs and convert them into functional requirements for corresponding produ...

AI Technical Summary

Problems solved by technology

The common artificial immune algorithm uses a random method to generate initial antibodies, which causes the algorithm to start with a low-quality solution. In addition, when constructing the affinity function, people often directly use the function to be sought as the affinity function. This solution is not applicable in personalized customization

Fixed crossover and mutation probabilities have the disadvantages of prematureness and poor stability when solving some complex problems, and how large the solution area is to search for the optimal solution has a certain impact on the performance of the algorithm

These factors hinder the further application of artificial immune algorithm in the field of personalized customization

Images