Intelligent system for products personalization and design using genetic algorithm

In the early manufacturing industry, characterized by mass production, the design was mainly concentrated on one or a type of products, less innovation was required, longer, and more substantial investment was allowed. To adapt to the user’s requirements for product personalization and diversification, and continuously expand the space for product innovation, this paper proposes an intelligent product design method. Traditional design theory is creatively combined with the proposed model to achieve the intended goal. The application models of two interactive genetic algorithms based on the compound fitness allocation strategy (HFAS) and the graded fitness allocation strategy are proposed, and the parameters of the compound fitness allocation strategy are analyzed. A case study of the proposed model is implemented, and two methods of Full Permutation and fuzzy evaluation are applied to evaluate the design results.