Abstract: With the development of science and technology, industrial construction has entered the era of 4.0 intelligent construction, and various algorithms have been widely applied in the modularization of production products. This study focuses on the modular optimization problem of complex products and establishes a hybrid genetic algorithm based on the ant colony algorithm framework. The new algorithm incorporates visibility analysis of the genetic algorithm, using the obtained solution as the pheromone source for the new algorithm to quickly obtain the optimal solution. The results showed that the algorithm could quickly achieve modularization of complex industrial products, adapt to products with a large number of parts and complex compositions, and obtain the optimal solution. The new algorithm reduced the running time of modular complex products by 35.06% compared to the particle swarm optimization algorithm. The new algorithm optimized the product design process for core components, reducing production costs by 23.46% and increasing production efficiency by 39.20%. Consequently, the novel algorithm modularizes complex products, thereby enhancing production efficiency and providing a novel intelligent method for the design process of complex products.

Yichun Shi and Qinhe Shi, “Modular Analysis of Complex Products Based on Hybrid Genetic Ant Colony Optimization in the Context of Industry 4.0” International Journal of Advanced Computer Science and Applications(IJACSA), 16(2), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160269

@article{Shi2025,
title = {Modular Analysis of Complex Products Based on Hybrid Genetic Ant Colony Optimization in the Context of Industry 4.0},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160269},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160269},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {2},
author = {Yichun Shi and Qinhe Shi}
}