Intelligent decision system based on the evidential reasoning approach and its applications

• Autorzy: Xu D. L. , Yang J. B.
• Języki publikacji: EN

Abstrakty

EN

Intelligent decision system (IDS) is a window-based software package that has been developed on the basis of the evidential reasoning (ER) approach, a recent development in handling hybrid multiple criteria decision analysis (MCDA) problems with uncertainties. In this paper, the evidential reasoning approach will be briefly described first, and its major differences from and the relationships with conventional MCDA methods will also be discussed. Then the main features, advantages and benefits of IDS will be demonstrated and explained using two application examples: supplier pre-qualification assessment and customer satisfaction survey analysis, which have been investigated as part of the research projects led by the authors and funded by the UK government and the EC. It is concluded in the paper that the ER approach can be used not only to deal with problems that traditional methods can solve, but also to model and analyse more complicated decision problems that traditional methods are incapable of handling.

Słowa kluczowe

EN

multicriteria decision support systems; knowledge management; intelligent decision system; evidential reasoning approach

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2005
• Tom: nr 3
• Strony: 73--80
• Opis fizyczny: Bibliogr. 16 poz., il.

Twórcy

autor

Xu D. L.

• Manchester Business School (East), The University of Manchester, PO Box 88, Manchester M60 1QD, United Kingom

autor

Yang J. B.

• Manchester Business School (East) The University of Manchester, PO Box 88 Manchester M60 1QD, United Kingdom

Bibliografia

• [1] V. Belton and T. J. Stewart, Multiple Criteria Decision Analysis – an Integrated Approach. Boston: Kluwer, 2002.
• [2] B. G. Buchanan and E. H. Shortliffe, Rule-Based Expert Systems. Reading: Addison-Wesley, 1984.
• [3] R. López de M´antaras, Approximate Reasoning Models. Chichester: Ellis Horwood, 1990.
• [4] P. Orponen, “Dempster’s rule of combination is # P-complete”, Artif. Intell., vol. 44, pp. 245–253, 1990.
• [5] G. Shafer, A Mathematical Theory of Evidence. Princeton: Princeton University Press, 1976.
• [6] C. H. R. Siow, J. B. Yang, and B. G. Dale, “A new modelling framework for organisational self-assessment: development and application”, AQS Qual. Manag. J., vol. 8, no. 4, pp. 34–47, 2001.
• [7] J. L. Teng, “Development of a supplier pre-qualification model for a UK company”. M.Sc. thesis, Manchester School of Management, UMIST, 2002.
• [8] T. van der Wiele, A. R. T. Williams, F. Kolb, and B. G. Dale, “Assessor training for the European Quality Award”, Qual. World Techn. Suppl., pp. 12–18, March 1995.
• [9] D. L. Xu and J. B. Yang, “Introduction to multi-criteria decision making and the evidential reasoning approach”. Manchester School of Management, University of Manchester Institute and Technology, May 2001.
• [10] J. B. Yang and P. Sen, “A general multi-level evaluation process for hybrid MADM with uncertainty”, IEEE Trans. Syst. Man Cyber., vol. 24, no. 10, pp. 1458–1473, 1994.
• [11] J. B. Yang and M. G. Singh, “An evidential reasoning approach for multiple attribute decision making with uncertainty”, IEEE Trans. Syst. Man Cyber., vol. 24, no. 1, pp. 1–18, 1994.
• [12] J. B. Yang, “Rule and utility based evidential reasoning approach for multiple attribute decision analysis under uncertainty”, Eur. J. Oper. Res., vol. 131, no. 1, pp. 31–61, 2001.
• [13] J. B. Yang, B. G. Dale, and C. H. R. Siow, “Self-assessment of excellence: an application of the evidential reasoning approach”, Int. J. Prod. Res., vol. 39, no. 16, pp. 3789–3812, 2001.
• [14] J. B. Yang and D. L. Xu, “On the evidential reasoning algorithm for multiattribute decision analysis under uncertainty”, IEEE Trans. Syst. Man Cyber., Part A: Systems and Humans, vol. 32, no. 3, pp. 289–304, 2002.
• [15] J. B. Yang and D. L. Xu, “Nonlinear information aggregation via evidential reasoning in multiattribute decision analysis under uncertainty”, IEEE Trans. Syst. Man Cyber., Part A: Systems and Humans, vol. 32, no. 3, pp. 376–393, 2002.
• [16] Z. J. Zhang, J. B. Yang, and D. L. Xu, “A hierarchical analysis model for multiobjective decision making”, in 4th IFAC/IFIP/ IFORS/IEA Conf. “Analysis, Design and Evaluation of Man-Machine System 1989”, Xian, China, 1989. Oxford: Pergamon, 1990, pp. 13–18.