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| Optimal Design Method of Complex System Based on Resource Optimization |
| ZHANG Rongfu1， WANG Jinqiang2， LIU Minxia1 |
| 1. School of Mechanical Engineering， Beijing Institute of Technology， Beijing 100081， China；
2. Jiangnan Electromechanical Design Institute， Guiyang 550025， Guizhou， China |
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Abstract To solve the resource optimisation problem in the modular design of complex systems, a hybrid optimisation method combining fuzzy C-means clustering, genetic algorithm, simulated annealing, and immune selection mechanism was proposed in this study. This method first used the fuzzy C-means clustering algorithm to analyse the correlation between component functional structures, generating initial module partitions. Then, it optimised the module partitions using an improved genetic algorithm. The integration of simulated annealing significantly enhanced the local search ability of the algorithm. At the same time, the immune selection mechanism maintained population diversity through operations including elite retention, gene exchange, and insertion mutation, further improving the algorithm's global search ability and stability. The results show that the proposed method significantly optimises the cohesion and coupling of modules and can effectively improve the quality and efficiency of modular design. In addition, the process presents an ideal balance between calculation speed and optimisation accuracy, which is particularly suitable for industrial scenarios having high requirements for independence, scalability and cost control.
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Received: 31 March 2025
Published: 15 July 2025
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2025, Vol. 8 
