Optimization of roadway support schemes with likelihood-based MABAC method

Whether a roadway support scheme is reasonable or not significantly affects the safety of workers and the mining efficiency of mines. This paper concentrates on the optimization of roadway support schemes with group decision making methods. At first, in order to convey the decision makers' preference more fully and aptly, assessment information for schemes is transformed into LNNs (linguistic neutrosophic numbers). For the purpose of overcoming the weakness of the extant comparison method, the likelihood of LNNs is advised. After that, an extended MABAC (multi-attributive border approximation area comparison) method based on likelihood is presented. Three stages are contained in this modified approach. Stage 1 aims to obtain the normalized decision making matrix; Stage 2 builds an inclusive criteria weight model to compute the weighted decision making matrix; Stage 3 gets the ranking order of alternatives by defining three approximation areas. Subsequently, a case study is given to confirm the practicability of the proposed method. At last, sensitive analysis and comparative analysis are conducted, followed by some discussions and conclusions. (C) 2019 Elsevier B.V. All rights reserved.