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Gold Science and Technology ›› 2022, Vol. 30 ›› Issue (2): 282-290.doi: 10.11872/j.issn.1005-2518.2022.02.078

• Mining Technology and Mine Management • Previous Articles     Next Articles

Optimization of Mining Method with Subjective and Objective Combination Weight TOPSIS Based on Game Theory

Longxin DENG(),Jianhong CHEN()   

  1. School of Resources and Safety Engineering,Central South University,Changsha 410083,Hunan,China
  • Received:2021-06-20 Revised:2021-09-22 Online:2022-04-30 Published:2022-06-17
  • Contact: Jianhong CHEN E-mail:841416210@qq.com;cjh@263.net

Abstract:

In the current optimization of mining methods, subjective components lead to more information loss, and the relative importance of evaluation indicators is unreasonable.This paper fully considered the results of the combination of comprehensive degree analysis method and fuzzy analytic hierarchy process-fuzzy extended analytic hierarchy process (FEAHP) and objective weight method CRITIC,used FEAHP to determine the subjective weight of each index in the optimization system of mining method.CRITIC algorithm was used to calculate the conflict between various indicators,so as to calculate the objective weight.Then,the principles of game theory was used to compromise the subjective and objective weights,and find their consistency to obtain a reasonable combination weight.Finally,combined with the real data of the alternatives,the distance between the four alternatives and the positive and negative ideal solutions is obtained by the distance measurement method in TOPSIS,and the relative patching progress of the four alternatives was calculated.The options of the upward approach cement filling method (Scheme 1), the shallow hole retention and subsequent filling method (Scheme 2), the upward horizontal layered filling method (Scheme 3) and the downward horizontal layered filling method (Scheme 4).The relative patching progress of the four alternatives are 0.4547,0.4441,0.5872,0.4072 respectively.It is concluded that the third scheme (upward horizontal stratified filling method) is the best,and the relative paste progress of 0.5872 also fully demonstrates that the upward horizontal stratified filling method has formed a strong contrast with the other three schemes,showing that the scheme meets the requirements of modern mining engineering for safety,low cost,and high profit,highlights its own advantages,and is consistent with mine examples and other experts’ research, indicating that the model is scientific and effective for mining optimization.

Key words: fuzzy extended analytic hierarchy process, CRITIC method, game theory, combination weights, TOPSIS, relative paste progress, mining method optimizations

CLC Number: 

  • TD802

Table 1

Language variables and their corresponding triangular fuzzy numbers"

语言变量三角模糊标度三角模糊互反标度
完全相同(JE)(1,1,1)(1,1,1)
同等重要(EI)(1/2,1,3/2)(2/3,1,2)
稍微重要(WMI)(1,3/2,2)(1/2,2/3,1)
明显重要(SMI)(3/2,2,5/2)(2/5,1/2,2/3)
非常重要(VSMI)(2,5/2,3)(1/3,2/5,1/2)
极端重要(AMI)(5/2,3,7/2)(2/7,1/3,2/5)

Table 2

Average random consistency index values"

判断矩阵阶数RI判断矩阵阶数RI
1061.24
2071.32
30.5881.41
40.991.4
51.12

Fig.1

Intersection between M1 and M2(Zhu et al.,1999)"

Fig.2

Framework diagram of mining method optimization evaluation system"

Table 3

Comprehensive evaluation index system for optimization of mining methods(Wang et al.,2013;Chen et al.,2017)"

评判指标C1C2C3C4
经济指标(P1采充总成本(X1) / (元·t-186.258.571.666.9
矿石回收率(X2 / %84838783
矿石贫化率(X3 / %710512
技术指标(P2采切比(X4) / (m3 ·k-1·t-136.1064.6057.5043.65
方案灵活适应性(X50.750.550.850.55
实施困难程度(X60.850.550.850.65
采场生产能力(X7) / (t·d-1144.3198.6201.8232
安全指标(P3采空区最大暴露面积(X8) / m2470822.4390470
通风条件(X90.850.750.850.75
爆破对边坡稳定性影响程度(X100.550.850.650.85

Table 4

O-P layer fuzzy comparison judgment matrix"

评判指标经济指标(P1技术指标(P2安全指标(P3
经济指标(P1(1,1,1)(1/2,1,3/2)(3/2,2,5/2)
技术指标(P2(2/3,1,2)(1,1,1)(1,3/2,2)
安全指标(P3(2/5,1/2,2/3)(1/2,2/3,1)(1,1,1)

Table 5

O-P layer clear matrix"

评判指标经济指标(P1技术指标(P2安全指标(P3
经济指标(P11.0001.0002.000
技术指标(P21.1111.0001.500
安全指标(P30.5110.6941.000

Table 6

P1-X layer fuzzy comparison judgment matrix"

评判指标X1X2X3
X1(1,1,1)(1/2,1,3/2)(1,3/2,2)
X2(2/3,1,2)(1,1,1)(1,3/2,2)
X3(1/2,2/3,1)(1/2,2/3,1)(1,1,1)

Table 7

P2-X layer fuzzy comparison judgment matrix"

评判指标X4X5X6X7
X4(1,1,1)(1/2,1,3/2)(1,3/2,2)(1,3/2,2)
X5(2/3,1,2)(1,1,1)(1,3/2,2)(1,3/2,2)
X6(1/2,2/3,1)(1/2,2/3,1)(1,1,1)(1/2,1,3/2)
X7(1/2,2/3,1)(1/2,2/3,1)(2/3,1,2)(1,1,1)

Table 8

P3-X layer fuzzy comparison judgment matrix"

评判指标X8X9X10
X8(1,1,1)(1/2,1,3/2)(3/2,2,5/2)
X9(2/3,1,2)(1,1,1)(1,3/2,2)
X10(2/5,1/2,2/3)(1/2,2/3,1)(1,1,1)

Table 9

Relative paste progress of four schemes"

方案di+di-Ei+排序
方案10.70400.58720.45472
方案20.75560.60380.44413
方案30.52690.74960.58721
方案40.75810.52070.40724
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