A model for decision making with missing, imprecise, and uncertain evaluations of multiple criteria

International Journal of Intelligent Systems

Volumn 28, Issue 2, 2013, Pages 152-184

  Ma, Wenjun ^a   Xiong, Wei ^a   Luo, Xudong ^a  

^a SUN YAT SEN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BELIEF FUNCTION; DEMPSTER'S RULE OF COMBINATION; DEMPSTER-SHAFER; EVALUATION INTERVAL; HIERARCHY PROCESS; INTERVAL-VALUED; MASS FUNCTIONS; MULTI-CRITERIA DECISION MAKING; MULTIPLE CRITERIA; OPTIMAL SOLUTIONS; PLAUSIBILITY FUNCTION; REAL ESTATE INVESTMENT; UNCERTAIN EVALUATION;

DECISION MAKING; DISTRIBUTION FUNCTIONS; INVESTMENTS; UNCERTAINTY ANALYSIS;

FUNCTION EVALUATION;

EID: 84870932434     PISSN: 08848173     EISSN: 1098111X     Source Type: Journal    
DOI: 10.1002/int.21562     Document Type: Article

References (72)

1. Hua Z, Gong B, Xu X,. A dsahp approach for multi-attribute decision making problem with incomplete information. Expert Syst Appl 2008; 34 (3): 2221-2227.
2. Xiong W, Ma W, Luo X,. An expected utility interval theory for decision-making under uncertainty of ambiguity: To avoid ambiguity and minimise regret. Technical report. Institute of Logic and Cognition, Sun Yat-sen Univerisity; 2012.
3. Yang J-B, Xu D-L,. On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty. IEEE Trans Systems, Man Cybernet, Part A 2002; 32 (3): 289-304.
4. Luo X, Jennings NR,. A spectrum of compromise aggregation operators for multi-attribute decision making. Artif Intell 2007; 171 (2-3): 161-184.
5. Dempster A,. Upper and lower probabilities induced by a multivalued mapping. In:, Yager R, Liu L, editors. Classic works of the Dempster-Shafer theory of belief functions. Stud Fuzziness Soft Comput 2008;219: 57-72.
6. Shafer G,. A mathematical theory of evidence. Princeton, NJ: Princeton University Press; 1976.
7. Saaty TL,. Analytic hierarchy process. Hoboken, NJ: Wiley; 2005.
8. Beynon M,. The role of the DS/AHP in identifying inter-group alliances and majority rule within group decision making. Group Decision Negotiation 2006; 15: 21-42.
9. Beynon M, Curry B, Morgan P,. The Dempster-Shafer theory of evidence: an alternative approach to multicriteria decision modelling. Omega 2000; 28 (1): 37-50.
10. Beynon M, Moutinho L, Veloutsou C,. A Dempster-Shafer theory based exposition of probabilistic reasoning in consumer choice. In:, Casillas J, Martnez-Lpez F, editors. Marketing intelligent systems using soft computing. Stud Fuzziness Soft Comput 2010; 258: 365-387.
11. Awasthi A, Chauhan SS,. Using AHP and Dempster-Shafer theory for evaluating sustainable transport solutions. Environ Model Software 2011; 26 (6): 787-796.
12. Beynon M,. DS/AHP method: a mathematical analysis, including an understanding of uncertainty. Eur J Oper Res 2002; 140 (1): 148-164.
13. Ma W, Xiong W, Luo X,. A D-S theory based AHP decision making approach with ambiguous evaluations of multiple criteria. In, Anthony P, Ishizuka M, Lukose D, editors. PRICAI 2012: Trends in artificial intelligence. Lect Notes Comput Sci 2012; 7458: 297-311.
14. George T, Pal NR,. Quantification of conflict in Dempster-Shafer framework: A new approach. Int J Gen Syst 1996; 24 (4): 407-423.
15. Liu W,. Analyzing the degree of conflict among belief functions. Artif Intell 2006; 170 (11): 909-924.
16. Didier D, Henri P,. A note on measures of specificity for fuzzy sets. Int J Gen Syst 1985; 10 (4): 279-283.
17. Ramer A,. Uniqueness of information measure in the theory of evidence. Fuzzy Sets Syst 1987; 24 (2): 183-196.
18. Jousselme A-L, Liu C, Grenier D, Bosse E,. Measuring ambiguity in the evidence theory. IEEE Trans Syst Man Cybernet, Part A 2006; 36 (5): 890-903.
19. Von Neumann J, Morgenstern O,. Theory of games and economic behavior. Princeton, NJ: Princeton University Press; 1944.
20. Strat TM,. Decision analysis using belief functions. Int J Approx Reason 1990; 4 (56): 391-417.
21. Savage LJ,. The theory of statistical decision. J Am Stat Asso 1951; 46 (253): 54-67.
22. Landman J,. Regret: The persistence of the possible. Oxford, UK: Oxford University Press; 1993.
23. Daniel E,. Risk, ambiguous, and the savage axioms. Q J Econ 1961; 75 (4): 643-669.
24. Treich N,. The value of a statistical life under ambiguity aversion. J Environ Econ Manage 2010; 59 (1): 15-26.
25. Beynon MJ,. Understanding local ignorance and non-specificity within the DS/AHP method of multi-criteria decision making. Eur J Oper Res 2005; 163 (2): 403-417.
26. Bragge J, Korhonen P, Wallenius H, Wallenius J,. Bibliometric analysis of multiple criteria decision making/multiattribute utility theory. In:, Ehrgott M, Naujoks B, Stewart TJ, Wallenius J, Fandel G, Trockel W, editors. Multiple criteria decision making for sustainable energy and transportation systems. Lect Notes Econ Math Syst 2010; 634: 259-268.
27. Wallenius J, Dyer JS, Fishburn PC, Steuer RE, Zionts S, Deb K,. Multiple criteria decision making, multiattribute utility theory: Recent accomplishments and what lies ahead. Manage Sci 2008; 54 (7): 1336-1349.
28. Xu B, Tao C, Xia H,. A method for dam safety evaluation based on Dempster-Shafer theory. In:, Huang D-S, Zhang X, Garca Zhang L, editors. Advanced intelligent computing theories and applications, with aspects of artificial intelligence. Lect Notes Comput Sci 2010; 6216: 580-589.
29. Yang GM, Jia WB,. Research to health diagnose model of gate and hoist machinery based on AHP. Adv Mater Res 2011; 287-290: 3036-3042.
30. Xie Y, Yi S, Cao Y, Lu Y,. Uncertainty information fusion for flood risk assessment based on DS-AHP method. In: 19th Int Conf on Geoinformatics; 2011. pp 1-6.
31. Kou G, Sun Q, Peng Y,. An entropy-weighted clustering method for environmental pollution assessment in China. In:, Shi Y, Wang S, Kou G, Wallenius J, Fandel G, Trockel W, editors, Lect Notes Econ Math Syst 2011; 648: 177-188.
32. Luo X, Jennings NR, Shadbolt N, Leung H-f, Lee JH-M,. A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments. Artif Intell 2003; 148 (1-2): 53-102.
33. Keeney RL, Raiffa H,. Decisions with multiple objectives. Cambridge, UK: Cambridge University Press; 1993.
34. Saaty TL,. Theory and applications of the analytic network process: Decision making with benefits, opportunities, costs, and risks. RWS Publications; University of Pittsburgh, Pittsburgh, USA 2005.
35. Yager RR, Rybalov A,. Uninorm aggregation operators. Fuzzy Sets Syst 1996; 80 (1): 111-120.
36. Yager RR,. On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans Syst Man Cybernet 1988; 18 (1): 183-190.
37. José F, Salvatore G, Matthias E,. Multiple criteria decision analysis: State of the art surveys. Boston, MA: Kluwer; 2005.
38. Dylan J, Mehrdad T,. Practical goal programming. New York: Springer; 2010.
39. Grossmann IE, Guilln-Goslbez G,. Scope for the application of mathematical programming techniques in the synthesis and planning of sustainable processes. Comput Chem Eng 2010; 34 (9): 1365-1376.
40. Maringanti C, Chaubey I, Arabi M, Engel B,. Application of a multi-objective optimization method to provide least cost alternatives for NPS pollution control. Environ Manage 2011; 48: 448-461.
41. Pan L, Luo X, Meng X, Miao C, He M, Guo X,. A two-stage winwin multiattribute negotiation model: Optimization and then concession. Comput Intell 2012:DOI: 10.1111/j.1467-8640.2012.00434.x.
42. Evans JP, Steuer RE,. A revised simplex method for linear multiple objective programs. Math Program 1973; 5: 54-72.
43. Zionts S, Wallenius J,. An interactive programming method for solving the multiple criteria problem. Manage Sci 1976; 22 (6): 652-663.
44. Zitzler E, Laumanns M, Bleuler S,. A tutorial on evolutionary multiobjective optimization. In:, Gandibleux X, Sevaux M, Srensen K, Tkindt V, Fandel G, Trockel W, editors. Metaheuristics for multiobjective optimisation. Lect Notes Econ Math Syst 2004; 535: 3-37.
45. Luo X, Zhang C, Jennings NR,. A hybrid model for sharing information between fuzzy, uncertain and default reasoning models in multi-agent systems. Int J Uncertain Fuzziness Knowl-Based Syst 2002; 10 (4): 401-450.
46. Zadeh LA,. Fuzzy sets. Inform Control 1965; 8 (3): 338-353.
47. Kahraman C,. Fuzzy multi-criteria decision making: Theory and applications with recent developments, 1 ed. New York: Springer; 2008.
48. Klir GJ, Folger TA,. Fuzzy sets, uncertainty, and information. Upper Saddle River, NJ: Prentice Hall; 1988.
49. Luo X, Lee JH-m, Leung H-f, Jennings NR,. Prioritised fuzzy constraint satisfaction problems: axioms, instantiation and validation. Fuzzy Sets Syst 2003; 136 (2): 151-188.
50. Magoč T, Wang X, Modave F,. Application of fuzzy measures and interval computation to financial portfolio selection. Int J Intell Syst 2010; 25 (7): 621-635.
51. Tan C, Chen X,. Induced intuitionistic fuzzy Choquet integral operator for multicriteria decision making. Int J Intell Syst 2011; 26 (7): 659-686.
52. Xu Z, Yager RR,. Dynamic intuitionistic fuzzy multi-attribute decision making. Int J Approx Reason 2008; 48 (1): 246-262.
53. Yager RR,. Concepts, theory, and techniques a new methodology for ordinal multiobjective decisions based on fuzzy sets. Decis Sci 1981; 12 (4): 589-600.
54. Yager RR,. Multiple objective decision-making using fuzzy sets. Int J Man-Machine Stud 1977; 9 (4): 375-382.
55. Greco S, Matarazzo B, Slowinski R,. Rough approximation of a preference relation by dominance relations. Eur J Oper Res 1999; 117 (1): 63-83.
56. Greco S, Matarazzo B, Slowinski R,. Rough sets theory for multicriteria decision analysis. Eur J Oper Res 2001; 129 (1): 1-47.
57. Greco S, Matarazzo B, Slowinski R,. Rough sets methodology for sorting problems in presence of multiple attributes and criteria. Eur J Oper Res 2002; 138 (2): 247-259.
58. Lahdelma R, Salminen P, Hokkanen J,. Locating a waste treatment facility by using stochastic multicriteria acceptability analysis with ordinal criteria. Eur J Oper Res 2002; 142 (2): 345-356.
59. Lahdelma R, Salminen P,. Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis. Eur J Oper Res 2002; 141 (2): 454-469.
60. Guo M, Yang J-B, Chin K-S, Wang H-W, Liu X-B,. Evidential reasoning approach for multiattribute decision analysis under both fuzzy and interval uncertainty. IEEE Trans Fuzzy Syst 2009; 17 (3): 683-697.
61. Siow CHR, Yang JB, Ge Dale B,. A new modelling framework for organisational self-assessment: development and application. Qual Manage J 2001; 8 (4): 34-47.
62. Wang Y-M, Yang J-B, Xu D-L,. Environmental impact assessment using the evidential reasoning approach. Eur J Oper Res 2006; 174 (3): 1885-1913.
63. Wang Y-M, Yang J-B, Xu D-L, Chin K-S,. The evidential reasoning approach for multiple attribute decision analysis using interval belief degrees. Eur J Oper Res 2006; 175 (1): 35-66.
64. Xu D-L, Yang J-B, Wang Y-M,. The evidential reasoning approach for multi-attribute decision analysis under interval uncertainty. Eur J Oper Res 2006; 174 (3): 1914-1943.
65. Kreps DM,. Notes on the theory of choice. Westview Press; London 1988.
66. Deng Chan FTS,. A new fuzzy Dempster MCDM method and its application in supplier selection. Expert Syst Appl 2011; 38 (8): 9854-9861.
67. Kahneman D, Tversky A, editors,. Choices, values, and frames. Cambridge, UK: Cambridge University Press; 2000.
68. Kahneman D,. A perspective on judgment and choice: Mapping bounded rationality. Am Psychol 2003; 58 (9): 697-720.
69. Bhushan N, Rai K,. Strategic decision making: Applying the analytic hierarchy process. London: Springer; 2004.
70. Luo X, Miao C, Jennings NR, He M, Shen Z, Zhang M,. KEMNAD: A knowledge engineering methodology for negotiating agent deveploment. Comput Intell 2012; 28 (1): 51-105.
71. Ricci RG, Mesiar R,. Multi-attribute aggregation operators. Fuzzy Sets Syst 2011; 181 (1): 1-13.
72. Yu X, Xu Z, Liu S, Chen Q,. Multicriteria decision making with 2-dimension linguistic aggregation techniques. Int J Intell Syst, 2012; 27 (6): 539-562.