The state of equipment resources in cloud manufacturing environment is highly dynamic, and traditional resource selection methods are difficult to adapt to the complex and changing manufacturing environment. Changes in the service capacity of equipment resources lead to fluctuations in the quality of task service and affect the stability of the manufacturing process. In this paper, a dynamic selection strategy for equipment resources in cloud manufacturing environment based on multi-intelligence body evolutionary algorithm is proposed to solve the problem of service quality fluctuation caused by changes in the service capability of equipment resources during the execution of manufacturing tasks. The study establishes a mathematical model for cloud manufacturing equipment resource selection, comprehensively considers total time, total cost and service quality multi-objective optimization, and achieves dynamic resource preference through intelligent body grid neighborhood competition and self-learning mechanism. The dynamic evolution model of cloud manufacturing task service quality considering the influence of resource service capability change is further constructed, and the dynamic resource selection strategy and the minimum QoS requirement checking mechanism are designed to guarantee the stable control of the system. Simulation results show that the proposed algorithm outperforms the comparison algorithm in terms of convergence, solution efficiency and solution quality, and the average running time is only 2.63 seconds, which is 50% faster than the NSGA-II algorithm; under the level 5 interference level, the shortest processing time of this paper’s strategy is 3.58 hours, and the lowest cost is $271.44, and the quality of service satisfaction is 88.17%, which is superior to the NSGA-II algorithm. The case study verifies the application value of the proposed method in the actual cloud manufacturing environment, and provides new ideas to improve the resource allocation efficiency and stability of cloud manufacturing system.
