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Journal of System Simulation

Abstract

Abstract: In the process of cloud manufacturing, the incomplete information status and the mutual competition and restriction relationship between cloud platform operator and demander lead to the difficult choice of manufacturing services. A cloud manufacturing swarm intelligent optimization method based on incomplete information game model is proposed. A static game model based on incomplete information is established for the interest competition between demand-side and cloud platform, with the goal of rationally pursuing the maximization of their own revenue function. The competition rules between demand-side and cloud platform are proposed, which are introduced into nature through Harsanyi transformation and converted into a dynamic game under complete information to obtain Bayesian extended formula, and the existence and uniqueness of Bayesian Nash equilibrium are proved. A particle swarm optimization algorithm based on the update of Gaussian function and perturbation strategy is proposed to solve the above model. The simulation shows that the improved algorithm has faster convergence rate and higher total revenue of cloud manufacturing system compared with the other algorithms, and the incomplete information game model can take into account different types of demand side to improve the total revenue of cloud manufacturing system.

First Page

915

Last Page

928

CLC

TP391.9

Recommended Citation

Zhang Kunpeng, Wang Yan, Ji Zhicheng. Intelligent Optimization Method of Cloud Manufacturing Swarm Based on Incomplete Information Game[J]. Journal of System Simulation, 2024, 36(4): 915-928.

Corresponding Author

Wang Yan

DOI

10.16182/j.issn1004731x.joss.22-1500

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