Research on industrial product design optimization based on simulation and genetic algorithm

In response to the rapidly developing market demand, this paper proposes the use of genetic algorithms in industrial product design optimization under simulation environment.Design the product base gene coding, use the fitness function to determine the fitness value of different individuals, the genetic operator to support the optimization of industrial product design, by clarifying the optimal individual in the population in order to determine the optimization of industrial product design to meet the conditions.Then build up the industrial product design system based on genetic algorithm, plan the functional modules such as product information collection and coding, genetic generation of product solutions, and formulate the system process and function realization method.Exploring the performance of this paper's industrial product design model in the simulation environment, this paper's model in the operation efficiency, convergence speed and other aspects of performance are better than its other comparison model, in the iteration to about 300 times to achieve convergence.In the application practice of this paper's design system, the 2 R values of this paper's system are close to 1, and the RMSE values of each design parameter are lower than 0.5, and the average product quality score reaches 0.157, which is excellent in real-world applications.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-18
DOI
https://doi.org/10.61091/jcmcc127b-207
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on industrial product design optimization based on simulation and genetic algorithm

Journal of Combinatorial Mathematics and Combinatorial Computing
Industrial Technology and Control Systems
article

Research on industrial product design optimization based on simulation and genetic algorithm

article en

Abstract

In response to the rapidly developing market demand, this paper proposes the use of genetic algorithms in industrial product design optimization under simulation environment.Design the product base gene coding, use the fitness function to determine the fitness value of different individuals, the genetic operator to support the optimization of industrial product design, by clarifying the optimal individual in the population in order to determine the optimization of industrial product design to meet the conditions.Then build up the industrial product design system based on genetic algorithm, plan the functional modules such as product information collection and coding, genetic generation of product solutions, and formulate the system process and function realization method.Exploring the performance of this paper's industrial product design model in the simulation environment, this paper's model in the operation efficiency, convergence speed and other aspects of performance are better than its other comparison model, in the iteration to about 300 times to achieve convergence.In the application practice of this paper's design system, the 2 R values of this paper's system are close to 1, and the RMSE values of each design parameter are lower than 0.5, and the average product quality score reaches 0.157, which is excellent in real-world applications.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127b
Openalex Percentile: Top 92%
Industrial Technology and Control Systems
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