At present, partnership risk management is the key to affecting the success of R&D projects. Therefore, reasonably evaluating risk management capabilities of partners has become a critical issue of enterprises in project risk management. In view of the environmental uncertainty and information ambiguity in project risk management, this paper proposes a dynamic grey target decision making method with interval gray numbers based on error propagation and orthogonal projection, and applies it to evaluate risk management capability of partners in R&D projects. In this proposed method, firstly an error propagation model is used to determine attribute weight intervals; and according to the off-target deviation degree theory, decision-making information in all of the periods is aggregated, obtaining a comprehensive decision matrix; then the concept of time degree is introduced, and a multi-objective nonlinear programming model is established to determine time weights; and the ranking of alternatives is obtained by orthogonal projection method. Finally, the feasibility and effectiveness of the proposed method are verified by a numerical example.
YetB., ConstantinouA., FentonN., NeilM., LuedelingE. and ShepherdK., A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study, Expert Systems with Applications60 (2016), 141–155.
2.
RodriguezA., OrtegaF. and ConcepcionR., A method for the evaluation of risk in IT projects, Expert Systems with Applications45 (2016), 273–285.
3.
QaziA., QuigleyJ., DicksonA. and KirytopoulosK., Project Complexity and Risk Management (ProCRiM): Towards modelling project complexity driven risk paths in construction projects, International Journal of Project Management34 (2016), 1183–1198.
4.
MuS., ChengH., ChohrM. and PengW., Assessing risk management capability of contractors in subway projects in mainland China, International Journal of Project Management32 (2014), 452–460.
5.
XuZ.S., On multi-period multi-attribute decision making, Knowledge-Based Systems21 (2008), 164–171.
6.
LinY.H., Dynamic multi-attribute decision making model with grey number evaluations, Expert Systems with Applications21 (2008), 1638–1644.
7.
LuoD. and WangX., The multi-attribute grey target decision method for attribute value within three-parameter interval grey number, Applied Mathematical Modelling36 (2012), 1957–1963.
8.
ZhuJ.J. and HipelK.W., Multiple stages grey target decision making method with incomplete weight based on multi-granularity linguistic label, Information Sciences212 (2012), 15–32.
9.
WuJ., DongF.H. and LiangC.Y., Two-phase optimized model for interval multi-attribute decision making based on projection method, Systems Engineering and Electronics30 (2008), 2393–2397.
10.
YanS.L., LiuS.F. and FangZ.G., Dynamic risk grey target decision making method based on cumulative prospect theory, Control and Decision28 (2013), 1655–1660+1666.
11.
LiuY., ForrestJ. and LiuS.F., Multi-objective grey target decision-making based on Prospect theory, Control and Decision28 (2013), 345–350.
12.
LiangY.H., GuoP. and ZhuY.M., A sample-set based on interval gray target classification and decision-making model and its applications, Chinese Journal of Management Science22 (2014), 98–103.
13.
SuZ.X., ChenM.Y., XiaG.P. and WangL., An interactive method for dynamic intuitionistic fuzzy multi-attribute group decision making, Expert Systems with Applications38 (2011), 15286–15295.
14.
ParkJ.H., ChoH.J. and KwunY.C., Extension of the VIKOR method to dynamic intuitionistic fuzzy multiple attribute decision making, Computers and Mathematics with Applications65 (2013), 731–744.
15.
SadiqR. and TesfamariamS., Probability density functions based weights for ordered weighted averaging (OWA) operators: An example of water quality indices, European, Journal of Operational Research182 (2007), 1350–1368.
16.
XuZ. and ChenJ., Binomial distribution based approach to deriving time series weights, in: 2007 IEEE International Conference on Industrial Engineering and Engineering Management, IEEE, 2007, pp. 154–158.
17.
XuZ.S. and YagerR.R., Dynamic intuitionistic fuzzy multi-attribute decision making, International Journal of Approximate Reasoning48 (2008), 246–262.
18.
XuZ.S., On multi-period multi-attribute decision making, Knowledge-Based Systems21 (2008), 164–171.
19.
TanC. and ChenX., Dynamic similarity measures between intuitionistic fuzzy sets and its application, International Journal of Fuzzy System16 (2014), 511–519.
20.
SunB. and XuX.F., A dynamic stochastic decision-making method based on discrete time sequences, Knowledge-Based Systems105 (2016), 23–28.
21.
WangJ.Q., LiK.J. and ZhangH.Y., Interval-valued intuitionistic fuzzy multi-criteria decision-making approach based on prospect score function, Knowledge-Based Systems27 (2012), 119–125.
22.
WangH.H., ZhuJ.J. and FangZ.G., Grey target cluster decision method on linguistic evaluation case-based, Systems Engineering-Theory & Practice33 (2013), 3172–3181.
23.
ZengB., LiuS.F. and LiC., Grey target decision-making model of interval grey number based on cobweb area, Systems Engineering and Electronics35 (2013), 2329–2334.
24.
QinJ.D., LiuX.W. and PedryczW., An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment, Knowledge-Based Systems86 (2015), 116–130.
25.
ChenT.Y., The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making, Applied Soft Computing26 (2015), 57–73.
26.
YuF., Evaluation on industrial efficiency of the developed eastern region with a grey target – TOPSIS-based approach, Statistics and Decision07 (2012), 65–67.
27.
DaiW.Z. and LiJ.L., Off-target deviation degree method for grey multi-attribute group decision-making, Systems Engineering-Theory & Practice34 (2014), 787–792.
28.
KeC.Y., LiJ.J. and LiuZ.L., A new approach for characterizing the intermediate feature of alpha-chymotrypsin refolding by hydrophobic interaction chromatography, International Journal of Molecular Sciences10 (2009), 616–628.
29.
LiuZ.L., XiaoZ.P. and MasukoS., Mass balance analysis of contaminated heparin product, Analytical Biochemistry408 (2011), 147–156.
30.
YangZ.C., Error theroy, Chinese Industrial University Press, Chang Sha, 1987.
31.
YoonK., The propagation of errors in multiple-attribute decision analysis: A practical approach, Journal of the Operational Rescarch Society40 (1989), 681–686.
32.
YouT.H. and GaoM.L., An error-analysis-based approach for multi-attribute decision making with interval numbers, Journal of Systems & Management23 (2014), 224–228.
33.
YagerR.R., On ordered weighted averaging aggregation operators in multicriteria decision making, IEEE Transactions on Systems, Man, and Cybernetics18 (1988), 183–190.
34.
HuaX.Y. and TanJ.X., Revised TOPSIS method based on vertical projection distance-vertical projection method, Systems Engineering-Theory & Practice1 (2004), 114–119.
