The traditional bilateral matching model of R & D personnel and project manager does not use ant colony optimization algorithm to solve the problem, which leads to low matching effect and matching satisfaction, and the complexity of the model is large. Therefore, a bilateral matching model between R & D personnel and project manager based on ant colony algorithm is designed and proposed, to improve the calculation model of attribute matching degree, and formulate the evaluation principles of stable matching and current optimal matching. The pheromone is updated by ant colony optimization algorithm. According to the influence function, the impact of demand change on matching individuals in the bilateral matching of multi-attribute researchers and project economy is dynamically measured. With the help of the bilateral matching model, the set of individuals who participate in the matching again after demand change is determined, and the best matching result is obtained. Simulation results show that the proposed model can effectively improve the satisfaction of matching results and matching efficiency, and effectively reduce the matching complexity.

传统的研发人员和项目经理的双边匹配模型没有使用蚁群优化算法解决问题，导致匹配效果和匹配满意度低，模型复杂度大。为此，设计并提出了基于蚁群算法的研发人员与项目经理双边匹配模型，完善属性匹配度计算模型，制定稳定匹配和当前最优匹配的评价原则。信息素由蚁群优化算法更新。根据影响函数，动态衡量需求变化对多属性研究者与项目经济双边匹配中匹配个体的影响。借助双边匹配模型，确定需求变化后再次参与匹配的个体集合，得到最佳匹配结果。仿真结果表明，所提模型能够有效提高匹配结果的满意度和匹配效率，有效降低匹配复杂度。