关键词: 工业互联网, 多边匹配, 环境效益, 农机供应链

Abstract:  From the perspective of improving the environmental benefits of the agricultural machinery supply chain, this paper comprehensively considers the energy consumption of industrial Internet resources and the characteristics of knowledge accumulation of multiple participation tasks. Based on the influence of learning rate on service quality, a onetoone multilateral matching model is established to maximize the service satisfaction of agricultural machinery service demander, agricultural machinery service provider, and platform energy consumption. Taking the production of a certain agricultural machinery cover mold on the industrial Internet collaborative management platform of Tianjin agricultural machinery supply chain as an example, the optimal matching scheme is obtained. Compared with the general matching model, the model without considering the learning effect, and the model without considering the energy consumption, the number of nondominant solutions in this model is 6, which is more than the other three models. At the same time, when considering the learning effect, the agricultural machinery manufacturing service with a higher learning rate is selected to complete the task. When considering the energy consumption, the low energy consumption agricultural machinery cloud manufacturing service combination is selected to complete the task. This means that in the Industrial Internet environment, considering both the learning effect and energy consumption of agricultural machinery cloud manufacturing services in the agricultural machinery supply chain in the process of bilateral matchingis more in line with the actual industry needs and can achieve a winwin situation between the environmental performance and economic performance.

Key words:  Industrial Internet, multilateral matching, environmental benefits, agricultural machinery supply chain