Decision model of roof support based on R2-MOEA/D algorithm

The existing roof support decision methods either analyze safety factors one-sidedly or assign weights to index objectively, fail to assign weight coefficients effectively, and cannot meet the demand of high-dimensional multi-objective roof case decision. In order to solve this problem, a decision model of roof support based on R2 index differential high-dimensional multi-objective evolution (R2-MOEA/D) algorithm is proposed by analyzing the roof weighting index. Firstly, the model defines the index attributes for the roof weighting state, establishes the roof index knowledge base, and calculates the conditional index in the knowledge base using analytic hierarchy process and entropy method, and obtains the subjective and objective weights of the index. Secondly, the model introduces the weight matrix on the basis of determining the subjective and objective weights to construct the roof multi-objective decision model which based on R2-MOEA/D algorithm. Finally, based on the R2-MOEA/D algorithm, the multi-objective problem is decomposed into multiple sub-problems, and the Chebyshev function is used as the R2 index ranking criterion for individual selection to obtain the Pareto optimal solution with better convergence and diversity, i.e., the conditional index roof case with the highest similarity. And its corresponding result attributes provide the support scheme for the decision of the accident case. The experimental results show that the R2-MOEA/D algorithm has the best overall effect in terms of the convergence and distribution of the data set compared with the NSGA2 algorithm, NSGA3 algorithm and RVEA algorithm, and improves the search capability in high-dimensional space. The feasibility evaluation of the decision model of roof support based on R2-MOEA/D algorithm is carried out through the roadway 2-6011 and roadway 10-4151 in Sanjiaohe Coal Mine, Huozhou, Shanxi. The results show that the solution retrieved by R2-MOEA/D algorithm is in line with the actual support situation of the coal mine.