Multi-attributed decision making for mining methods based on grey system and interval numbers

LIU Lang(刘浪), CHEN Jian-hong(陈建宏), WANG Ge-ming(王革民), LAO De-zheng(劳德正)

(School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

Abstract:In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.

Key words:mining method; interval number; multi-attributed decision making; grey related analysis; correlation coefficient; normal distribution; ranking