<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper applies the combinatorial genetic algorithm to the design of industrial product forms to achieve the effect of industrial product form design innovation. The standard genetic algorithm is applied to industrial product design, and the optimal order of genetic optimization is constructed through continuous population genetics, combined with the minimum value of the objective function to construct the constraints of the innovative design of industrial products. Using the method of combinatorial optimization to integrate different elements in industrial product design, a coding method based on rows and columns is proposed for the set coverage problem of design elements. Analyzing the user’s preference for industrial product form design allows us to explore the demand direction of industrial product innovation design and formulate a suitable innovation design scheme. The results show that the consensus satisfaction of hair dryer form design in genetic optimization 2nd and 9th are higher than 0.8. When users are stimulated by like and dislike sample pictures, there is no significant difference in the average response time, p=0.337>0.05, and the difference in the average response time of the users is more significant p=0.020&lt;0.05 when they are confronted with the preferred design shape.</p>
</abstract>

This paper applies the combinatorial genetic algorithm to the design of industrial product forms to achieve the effect of industrial product form design innovation. The standard genetic algorithm is applied to industrial product design, and the optimal order of genetic optimization is constructed through continuous population genetics, combined with the minimum value of the objective function to construct the constraints of the innovative design of industrial products. Using the method of combinatorial optimization to integrate different elements in industrial product design, a coding method based on rows and columns is proposed for the set coverage problem of design elements. Analyzing the user’s preference for industrial product form design allows us to explore the demand direction of industrial product innovation design and formulate a suitable innovation design scheme. The results show that the consensus satisfaction of hair dryer form design in genetic optimization 2nd and 9th are higher than 0.8. When users are stimulated by like and dislike sample pictures, there is no significant difference in the average response time, p=0.337>0.05, and the difference in the average response time of the users is more significant p=0.020<0.05 when they are confronted with the preferred design shape.

Research on Morphological Innovation Design of Industrial Products Based on Combinatorial Genetic Algorithm

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper applies the combinatorial genetic algorithm to the design of industrial product forms to achieve the effect of industrial product form design...

Research on Morphological Innovation Design of Industrial Products Based on Combinatorial Genetic Algorithm

Online veröffentlicht: 20. Dez. 2023

Seitenbereich: -

Eingereicht: 21. März 2023

Akzeptiert: 30. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01557

Schlüsselwörter
Combinatorial Genetic Algorithm, Fitness Function, Combinatorial Optimization, Coding Method, Industrial Product Design

© 2023 Yan Han, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on Morphological Innovation Design of Industrial Products Based on Combinatorial Genetic Algorithm

Online veröffentlicht: 20. Dez. 2023

Seitenbereich: -

Eingereicht: 21. März 2023

Akzeptiert: 30. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01557

SchlüsselwörterCombinatorial Genetic Algorithm, Fitness Function, Combinatorial Optimization, Coding Method, Industrial Product Design

© 2023 Yan Han, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Combinatorial Genetic Algorithm, Fitness Function, Combinatorial Optimization, Coding Method, Industrial Product Design