Eliciting dual interval probabilities from interval comparison matrices

Information Sciences

Volumn 190, Issue , 2012, Pages 17-26

  Guo, Peijun ^a   Wang, Yuanbin ^a  

^a YOKOHAMA NATIONAL UNIVERSITY   (Japan)

Author keywords

Interval probabilities; Linear programming problem; Uncertainty modeling

Indexed keywords

BAYESIAN NETWORKS; LINEAR PROGRAMMING; MATRIX ALGEBRA; PRODUCT DEVELOPMENT; UNCERTAINTY ANALYSIS;

INCLUSION RELATION; INTERVAL COMPARISON MATRIX; INTERVAL COMPARISONS; INTERVAL PROBABILITY; LINEAR PROGRAMMING PROBLEM; NEW PRODUCT DEVELOPMENT; PAIR-WISE COMPARISON; UNCERTAINTY MODELING;

PROBABILITY;

EID: 84865717833     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2011.12.014     Document Type: Article

References (31)

1. D. Berleant, F.G. Cozman, O. Kosheleva, V. Kreinovich, Dealing with imprecise probabilities: interval-related talks at ISIPTA'05, Reliable Computing 12 (2006) 153-165.
2. A. Cano, S. Moral, Using probability trees to compute marginals with imprecise probabilities, International Journal of Approximate Reasoning 29 (2002) 1-46.
3. G. Coletti, S. Romano, The role of coherence in eliciting and handling imprecise probabilities and its application to medical diagnosis, Information Sciences 130 (2000) 41-65.
4. M. Danielson, L. Ekenberg, Computing upper and lower bounds in interval decision trees, European Journal of Operational Research 181 (2007) 808- 816.
5. L.M. de Campos, J.F. Huete, S. Moral, Probability intervals: A tool for uncertain reasoning, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 2 (1994) 167-196.
6. G. de Cooman, D. Aeyels, Supremum preserving upper probabilities, Information Sciences 118 (1999) 173-212.
7. A. Dempster, Upper and lower probabilities induced by a multivalued mapping, Annals of Mathematical Statistics 38 (1967) 325-339.
8. T. Ertay, D. Ruan, U.R. Tuzkaya, Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems, Information Sciences 176 (2006) 237-262.
9. P. Guo, H. Tanaka, Decision analysis based on fused double exponential possibility distributions, European Journal of Operational Research 148 (2003) 467-479.
10. P. Guo, H. Tanaka, Dual models for possibilistic regression analysis, Computational Statistics and Data Analysis 51 (2006) 253-266.
11. P. Guo, H. Tanaka, Decision making with interval probabilities, European Journal of Operational Research 203 (2010) 444-454.
12. I. Korkmaz, H. Gokcen, T. Cetinyokus, An analytic hierarchy process and two-sided matching based decision support system for military personnel assignment, Information Sciences 178 (2008) 2915-2927.
13. W.A. Lodwick, K.D. Jamison, Interval-valued probability in the analysis of problems containing a mixture of possibilistic, probabilistic, and interval uncertainty, Fuzzy Sets and Systems 159 (2008) 2845-2858.
14. E. Miranda, I. Couso, P. Gil, Approximations of upper and lower probabilities by measurable selections, Information Sciences 180 (2010) 1407-1417.
15. W. Pedrycz, M. Song, Analytic hierarchy process (AHP) in group decision making and its optimization with an allocation of information granularity, IEEE Transactions on Fuzzy Systems 19 (2011) 527-539.
16. T.L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, 1980.
17. A.A. Salo, Inconsistency analysis by approximately specified priorities, Mathematical and Computer Modelling 17 (1993) 123-133.
18. G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, Princeton, 1976.
19. M.J. Smithson, Human judgment and imprecise probabilities, available at , 1997.
20. K. Sugihara, H. Ishii, H. Tanaka, Interval priorities in AHP by interval regression analysis, European Journal of Operational Research 158 (2004) 745- 754.
21. H. Tanaka, K. Sugihara, Y. Maeda, Non-Additive measure by interval probability functions, Information Sciences 164 (2004) 209-227.
22. K. Tenekedjiev, Fuzzy-rational explanation of the Ellsberg paradox, Notes on Intuitionistic Fuzzy Sets 12 (2006) 39-52.
23. K. Tenekedjiev, N.D. Nikolova, Ranking discrete outcome alternatives with partially quantified uncertainty, International Journal of General Systems 37 (2008) 249-274.
24. M.C.M. Troffaes, Decision making under uncertainty using imprecise probabilities, International Journal of Approximate Reasoning 45 (2007) 7-29.
25. P. Walley, Statistical Reasoning with Imprecise Probability, Chapman and Hall, London, 1991.
26. P. Walley, Inferences from multinomial data: learning about a bag of marbles, Journal of the Royal Statistical Society B 58 (1996) 3-57.
27. Y.M. Wang, J.B. Yang, D.L. Xu, Interval weight generation approaches based on consistency test and interval comparison matrices, Applied Mathematics and Computation 167 (2005) 252-273.
28. Y.M. Wang, K.S. Chin, A linear programming approximation to the eigenvector method in the analytic hierarchy process, Information Sciences 181 (2011) 5240-5248.
29. K. Weichselberger, S. Pohlmann, A Methodology for Uncertainty in Knowledge-Based Systems, Lecture Notes in Artificial Intelligence, Springer-Verlag, 1990.
30. K. Weichselberger, The theory of interval-probability as a unifying concept for uncertainty, International Journal of Approximate Reasoning 24 (2000) 149-170.
31. R.R. Yager, V. Kreinovich, Decision making under interval probabilities, International Journal of Approximate Reasoning 22 (1999) 195-215.