A Linguistic Possibility-Probability Aggregation Model for decision analysis with imperfect knowledge

Applied Soft Computing Journal

Volumn 9, Issue 2, 2009, Pages 575-589

  Yuen, Kevin K F ^a   Lau, H C W ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Aggregation operators; Analytical Network Process (ANP); Decision making process; Linguistic Representation Model; R D project selection; Rating scales

Indexed keywords

DECISION MAKING; DECISION THEORY; KNOWLEDGE BASED SYSTEMS;

AGGREGATION OPERATORS; ANALYTICAL NETWORK PROCESS (ANP); DECISION MAKING PROCESS; LINGUISTIC REPRESENTATION MODEL; RATING SCALES;

LINGUISTICS;

EID: 58549107355     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2008.08.003     Document Type: Article

References (52)

1. Ansomebe F.J., and Aumann R.J. A definition of subjective probability. Ann. Math. Statist. 34 (1963) 199-255
2. Ben-Arieh D., and Cheng Z. Fuzzy group decision making. In: Badiru A.B. (Ed). Handbook of Industrial and Systems Engineering (2006), CRC Press Chapter 24
3. Blaikie N. Analyzing Quantitative Data (2003), Sage, London
4. Bonissin P.P., and Decker K.S. Selecting uncertainty. In: Kanal L.H., and Lemmer J.F. (Eds). Calculi and Granularity: An Experiment in Trading-Off Precision and Complexity (1986), Uncertainty In Artificial Intelligence, North-Holland 217-247
5. Bullen P.S., Mitrinovic D.S., and Vasic O.M. Means and Their Inequalities (1988), D. Reidel Publishing Company, Dordrecht
6. Chakraborty C., and Chakraboty D. A decision scheme based on OWA operator for an evaluation programme: an approximate reasoning approach. Appl. Soft Comput. 5 (2004) 45-53
7. Chen M.F., Tzeng G.-H., and Ding C.G. Combining fuzzy AHP with MDS in identifying the preference similarity of alternatives. Appl. Soft Comput. 8 1 (2008) 110-117
8. Coldrick S., Longhurst P., Ivey O., and Hannis J. An R&D options selection model for investment decisions. Technovation 25 (2005) 185-193
9. Duarte B.P.M., and Reis A. Developing a projects evaluation system based on multiple attribute value theory. Comput. Oper. Res. 33 (2006) 1488-1504
10. Dubois D., and Prade H. Possibility theory, probability theory and multiple-valued logics: a clarification. Ann. Math. Artif. Intel. 32 (2001) 25-66
11. Epstein L., and Zhang J.-K. Subjective probabilities on subjectively unambiguous events. Econometrica 69 (2001) 265-306
12. Fox C.R., and Clemen R.T. Subjective probability assessment in decision analysis: partition dependence and bias toward the ignorance prior. Manage. Sci. 51 9 (2005) 1417-1432
13. In: Gilovich T., Griffin D., and KahnemanD. (Eds). Heuristics and Bias: The Psychology of Intuitive Judgement (2002), Cambridge University Press, Cambridge, UK
14. Hakel M.D. How often is often?. Am. Psychol. 23 (1968) 533-534
15. Herrera F., Herrea-Viedma E., and Verdegay J.L. A rational consensus model in group decision making using linguistic assessments. Fuzzy Set Syst. 88 (1997) 31-49
16. Herrera F., and Martinez L. A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making. IEEE Trans. SMC B 31 2 (2001) 227-234
17. Hodge D.R., and Gillespie D.F. Phrase completions: an alternative to Likert scales. Social Work Res. 27 1 (2003) 45-55
18. Huang C.-C., Chu P.-Y., and Chiang Y.-H. A fuzzy AHP application in government-sponsored R&D project selection. Omega 36 6 (2008) 1038-1052
19. L. Hurwicz, Optimality criteria for decision making under ignorance. Cowles Commun. Discuss. Paper, Stat. No. 370, 1951.
20. Jeffrey L.R., Samuel B.G., and Randy H.C. Mean-Gini analysis in R&D portfolio selection. Eur. J. Oper. Res. 154 (2004) 157-169
21. Jindrich K., and Petr P. Decision support system for multicriterial R&D and information systems project selection. Eur. J. Oper. Res. 140 (2002) 434-446
22. In: Kahneman D., Sovic P., and Tversky A. (Eds). Judgement under Uncertainty: Heuristics and Bias (1982), Cambridge University Press, Cambridge, UK
23. Lauritizen S.L., and Nilsson D. Representing and solving decision problems with limited information. Manage. Sci. 47 9 (2001) 1235-1251
24. Li D.-F. Compromise ratio method of fuzzy multi-attribute group decision making. Appl. Soft Comput. 7 (2007) 807-817
25. Liesio J., Mild P., and Salo A. Preference programming for robust portfolio modeling and project selection. Eur. J. Oper. Res. 181 (2007) 1488-1505
26. Likert R. A technique for the measurement of attitudes. Arch. Psychol. 140 (1932) 55
27. Liou T.-S., and Wang M.-J.J. Subjective assessment of mental workload-a fuzzy linguistic multi-criteria approach. Fuzzy sets Syst. 62 (1994) 155-165
28. Luce R.D., and Raiffa H. Games and Decsions: Introduction and Critical Survey (1967), Wiley, New York
29. J.L. Marchial, Aggregation Operators for multicriteria decision aid. PhD. Dissertation. Universite De Liege, 1999.
30. Mikehailov L., and Tsvetinov P. Evaluation of services using fuzzy analytic hierarchy process. Appl. Soft Comput. 5 (2004) 23-33
31. Miller G.A. The magical number seven plus or minus two: some limits on our capacity of processing information. Psychol. Rev. 63 (1956) 81-97
32. Nau R.F. Uncertainty aversion with second-order utilities and probabilities. Manage. Sci. 52 1 (2006) 136-145
33. Osgood C.E., Suci G.J., and Tannenbaum P.H. The Measurement of Meaning (1957), University of Illinois Press, Urbana
34. Roubens M. Fuzzy sets decision analysis. Fuzzy Sets Syst. 90 (1997) 199-206
35. Saaty T.L. The Analytic Hierarchy Process (1980), McGraw-Hill, New York
36. Saaty T.L. Theory and Applications of the Analytic Network Process: Decision Making with Benefits, Opportunities, Costs and Risks (2005), RWS Publications
37. Simpson R. The specific meaning of certain terms indicating different degrees of frequency. Quart. J. Speech 30 (1944) 328-330
38. Smolikova R., and Wachowiak M.P. Aggregation operators for selection Problems. Fuzzy Sets Syst. 131 (2002) 23-34
39. Urso P.D., and Gastaldi T. An "orderwise" polynomial regression procedure for fuzzy data. Fuzzy Sets Syst. 130 (2002) 1-19
40. Vansant P., Bhattacharya A., Sarkar B., and Mukherjee S.K. Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF. Appl. Soft Comput. (2007) 1044-1054
41. Wewers M.E., and Lowem N.K. A critical review of visual analogue scales in the measurement of clinical phenomena. Res. Nurs. Health 13 (1990) 227-236
42. Yager R.R. On ordered weighted averaging aggregation operators in multi-criteria decision making. IEEE Trans. Syst., Man Cybernet. 18 (1988) 183-190
43. Yager R.R. Families of OWA operators. Fuzzy Sets Syst. 59 (1933) 125-148
44. Yager R.R. Non-numeric multi-criteria multi-person decision making. Group Decis. Negot. 2 (1993) 81-93
45. Yager R.R. Fuzzy modeling for intelligent decision making under uncertainty. IEEE Trans. SMC B 30 1 (2000) 60-70
46. Yeh Y., and Wickens C. Dissociation of performance and subjective measures of workload. Hum. Factors 30 (1988) 111-120
47. K.K.F. Yuen, A Compound Linguistic Ordinal Scales Model: A Breakthrough of The Magical Number Seven Plus or Minus two, Information Sciences, 2008, (submitted for publication).
48. K.K.F Yuen, Analytic Hierarchy Prioritization Process in the AHP Applications Development: A Prioritization Operator Selection Approach, Appl. Soft Comput. (submitted for publication).
49. K.K.F Yuen, H.C.W. Lau, Towards a distributed fuzzy decision making system, N.T. Nguyen (Eds.): KES-AMSTA 2008, Lecture Notes in Artificial Intelligence 4953 (2008), pp. 103-112.
50. K.K.F. Yuen, H.C.W. Lau, Software Vendor Selection using Fuzzy Analytic Hierarchy Process with ISO/IEC 9126, IAENG Int. J. Comput. Sci. 35 (3) (2008).
51. K.K.F Yuen, H.C.W. Lau, A fuzzy qualitative evaluation system, Int. J. Uncertain., Fuzz. Knowledge-Based Syst. (in press).
52. L.A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning, Inform. Sci. Part I (8) (1975) 199-249, Part II (8) (1975) 301-357, Part III (9) (1975) 43-86.