Multi-attribute Group Decision-making On The Promoting Main Body Of Clean Energy Of Green Town In Cold Region

In order to avoid repeating the same mistakes made by city the process of urbanization in the cities’ development, it is important to guide the rural energy consumption structure to a safe, economical, sustainable, clean consumption state, in the end of the Twelfth Five Years Plan and the crucial stage of deepening reform. Rural clean energy is an important issue to be solved in the progress of building of new socialist countryside and the promoting of green townThis paper studies promoting mechanism of rural clean energy in the cold area. The promoting of rural clean energy is a systematic project involving many decision-making body, and it is absent on the issue of conflict of interest among main body in current discussions. In order to effectively solve the conflict among the government sector, farmers, businesses and other stakeholders, it is very important to build a set of promoting mechanism for rural clean energy in cold area from the systemic and gaming simulation, which emphasizes the interactive among the decision-making body. It is necessary to build multi-attribute group decision-making combined with conflict analysis to avoid the invalidity of traditional mechanisms.Firstly, this paper constructs a number of rural clean energy propulsion mechanism through policy gaming, and applying Fuzzy AHP method to determine the attribute weights in order to give the players an optional set of policies. On this basis, this paper solves the model of multi-attribute group decision-making introducing conflict analysis to put forward a targeted and practical mechanism. Compared with other models, this model is quantifying the real problems which are hard to describe in a mathematical expression, while simulating and forecasting the final outcome of the conflict to help policy makers to analyze and judge.Based on the theoretical analysis, this article takes Xin’an town which belongs to Heilongjiang province as the example to make a empirical analysis. The model results indicate that the 11 th outcome is the optimal rural clean energy mechanisms for Xin’an town, and it is also Pareto efficient equilibrium.