Research on Optimization of Human-Skilled Matching of SMEs Based on Ant Colony Optimization Algorithm

Abstract

Human resource management plays a key role in the development of enterprises since the capital theory proposed. In this context, in this paper, based on the optimization of traditional ant colony algorithm, it is applied to enterprise human resource management, and its development mode optimization is studied. First of all, the ideas and advantages and disadvantages of the ant colony optimization algorithm are analyzed. Secondly, the optimized ant colony algorithm for human resource management is optimized, the Bayesian model of talent training constructed. Thirdly, through the expert assessment of the matching of people and posts, the ability index system is obtained. At last, the raw data of the algorithm test is used to test the algorithm. The test results show that the generalized regression ant colony algorithm optimized by ant colony algorithm is used to match the actual situation of the ant colony algorithm, which has certain advantages in solving such problems, playing a certain reference for the application of enterprise human resource management and computer algorithm.