Grey information coverage interaction relational decision making and its application

doi:10.23919/JSEE.2020.000013

Journal of Systems Engineering and Electronics ›› 2020, Vol. 31 ›› Issue (2): 359-369.doi: 10.23919/JSEE.2020.000013

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Grey information coverage interaction relational decision making and its application

Qinzi XIAO¹(), Miyuan SHAN^1,*(), Mingyun GAO¹(), Xinping XIAO²()

¹ School of Business Administration, Hunan University, Changsha 410082, China
² School of Science, Wuhan University of Technology, Wuhan 430070, China

Received:2019-03-21 Online:2020-04-30 Published:2020-04-30
Contact: Miyuan SHAN E-mail:qzxiao97@hnu.edu.cn;miyshan@163.com;wh14_gao@126.com;417267030@qq.com
About author:XIAO Qinzi was born in 1991. She received her M.S. degree from University of Birmingham, UK. She is pursuing her Ph.D. degree in management science and engineering from the School of Business Administration of Hunan University, China. Her research interests include operating system optimization, and quality management. E-mail: qzxiao97@hnu.edu.cn|SHAN Miyuan was born in 1962. He received his Ph.D. degree in management science and engineering from Central South University, China. He is a professor in the School of Business Administration of Hunan University, China. His research interests include operating system optimization, quality management, and supply chain management. E-mail: miyshan@163.com|GAO Mingyun was born in 1990. He received his B.S. and M.S degrees from Wuhan University of Technology, China. He is pursuing his Ph.D. degree in management science and engineering from the School of Business Administration of Hunan University, China. His research interests include operations research and management sciences, supply chain in finance and logistics optimization. E-mail: wh14_gao@126.com|XIAO Xinping was born in 1965. He received his Ph.D degree from Huazhong University of Science and Technology in 2002. He is a professor in the School of Science of Wuhan University of Technology. His research interests include grey system, systems engineering, and graph theory and control technology. E-mail: 417267030@qq.com
Supported by:
the National Natural Science Foundation of China(71871174);the National Natural Science Foundation of China(71571065);the National Natural Science Foundation of China(71671135);the National Social Science Fund of China(13FGL005);This work was supported by the National Natural Science Foundation of China (71871174; 71571065; 71671135) and the National Social Science Fund of China (13FGL005)

Abstract

Abstract:

This study aims to reflect the information coverage grey number and the interaction between attributes in grey relational decision making. Therefore, a multi-attribute decision method based on the grey information coverage interaction relational degree (GIRD) is proposed. Firstly, this paper defines the information coverage grey number, and establishes the GIRD model by using the Choquet fuzzy integral and grey relational principle. It proves that the proposed model not only is the general and unified form of the point relational degree, interval relational degree, mixed relational degree and grey fuzzy integral relational degree, but also can effectively deal with the interaction between attributes. Further, a decision making example of evaluating the industrial operation quality for 14 cities in Hunan province of China is provided to highlight the implementation, availability, and feasibility of the proposed decision model.

Key words: grey information coverage, interaction effect, fuzzy integral, grey relational degree, industrial quality evaluation

Qinzi XIAO, Miyuan SHAN, Mingyun GAO, Xinping XIAO. Grey information coverage interaction relational decision making and its application[J]. Journal of Systems Engineering and Electronics, 2020, 31(2): 359-369.

Figures/Tables 8

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References 30

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Soruce	Three types sum of squares	Degree of freedom	Square of mean	F	sig
Modified model	57 418 591.785$^{\ast }$	7	8 202 655.969	14.988	0.002
Intercept	83 779 746.887	1	83 779 746.887	153.087	0.000
$u_1 $	36 460 783.438	2	18 230 391.719	33.312	0.001
$u_2 $	12 660 102.319	2	6 330 051.159	11.567	0.009
$u_1 \times u_2 $	27 706 643.714	3	9 235 547.905	16.876	0.002
Error	3 283 616.777	6	547 269.463	-	-
Statistic	140 860 195.013	14	-	-	-
Total after adjustment	60 702 208.561	13	-	-	-

Indicator	$u_1 $	$u_2 $	$u_3 $	$u_4 $	$u_5 $	$u_6 $	$u_7 $	$u_8 $	$u_9 $	$u_{10} $	$u_{11} $	$u_{12} $	$u_{13} $	$u_{14} $	$u_{15} $	$u_{16} $	$u_{17} $	$u_{18} $	$u_{19} $	$u_{20} $	$u_{21}$	$u_{22}$
AHP weight	3.56	5.98	6.23	5.17	3.96	5.08	2.15	3.38	5.76	6.98	4.87	3.60	4.27	5.09	3.58	4.81	4.60	5.97	2.90	4.07	3.95	3.77

$\xi $	$\lambda $	$x_1 $	$x_2 $	$x_3 $	$x_4 $	$x_5 $	$x_6 $	$x_7 $	$x_8 $	$x_9 $	$x_{10} $	$x_{11} $	$x_{12} $	$x_{13} $	$x_{14} $
1	-0.99	0.957	0.904	0.814	0.705	0.611	0.714	0.911	0.789	0.676	0.781	0.697	0.620	0.760	0.646
0.580	-0.50	0.798	0.722	0.633	0.556	0.493	0.558	0.704	0.598	0.536	0.644	0.549	0.510	0.571	0.506
0.500	0	0.752	0.676	0.595	0.525	0.469	0.524	0.654	0.556	0.506	0.610	0.519	0.486	0.534	0.478
0.414	1	0.705	0.630	0.558	0.495	0.447	0.491	0.604	0.517	0.478	0.576	0.492	0.463	0.499	0.452
0.232	10	0.597	0.527	0.484	0.438	0.403	0.424	0.498	0.437	0.422	0.502	0.438	0.415	0.431	0.400
0.123	50	0.523	0.460	0.440	0.406	0.378	0.385	0.434	0.391	0.390	0.454	0.408	0.386	0.393	0.370
0.090	100	0.498	0.437	0.427	0.396	0.371	0.373	0.414	0.377	0.380	0.439	0.400	0.377	0.381	0.361
0.040	500	0.455	0.400	0.404	0.382	0.360	0.355	0.383	0.356	0.365	0.413	0.386	0.362	0.364	0.348

Liu's method [29]	$x_1 > x_{14} > x_2 > x_5 > x_{11} > x_{10} > x_3 > x_{13} > x_8 > x_6 > x_9 > x_4 > x_{12} > x_7 $
Fu's method [30]	$x_1 > x_3 > x_2 > x_{13} > x_7 > x_8 > x_4 > x_{11} > x_6 > x_9 > x_{10} > x_5 > x_{12} > x_{14} $
Proposed method	$x_1 > x_{10} > x_3 > x_2 > x_{11} > x_7 > x_4 > x_9 > x_{13} > x_{12} > x_5 > x_8 > x_6 > x_{14} $

Grey information coverage interaction relational decision making and its application

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