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The problem of objective ranking: foundations, approaches and applications

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Języki publikacji
EN
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EN
The paper starts with the discussion of the issue of objectivity versus subjectivity, stressing that while an absolute objectivity is not attainable, nevertheless trying to be as objective as possible constitutes a higher value, necessary for hard science and technology. Dangers and errors of the subjectivist reduction of objectivity to power and money attempted by the postmodern sociology of science are discussed. Then we turn to the problem of subjective versus objective decision analysis and ranking. It is shown that while all classical decision theory aims at a rational analysis and support of subjective decisions, there are important application cases, particularly in managerial problems, when the decision maker prefers to avoid specifying her/his preferences and needs decision analysis - e.g., ranking of decision options - that is as objective as possible. An approach to decision support that might be easily adapted for such objective ranking is the reference point methodology; its application is shown on examples. One of these examples is actually not an application of the methodology, but a real life problem that motivated the development of objective ranking. The examples illustrate that objective ranking might be important for management, including also management of telecommunication networks.
Rocznik
Tom
Strony
15--23
Opis fizyczny
Bibliogr. 28 poz., rys., tab.
Twórcy
Bibliografia
  • [1] R. I. Ackoff, “Towards a behavioural theory of communication”, in Modern Systems Research for the Behavioural Scientist, W. Buckey, Ed. Chicago: Aldine, 1957.
  • [2] L. Bertallanfy, “General systems theory”, Gener. Syst., vol. 1, pp. 1–10, 1956.
  • [3] M. Ehrgott and D. Tenfelde-Podehl, Nadir Values: Computation and Use in Compromise Programming. Universität Kaiserslautern Fachbereich Mathematik, 2000.
  • [4] M. Foucault, The Order of Things: An Archeology of Human Sciences. New York: Routledge, 1972.
  • [5] J. Granat, M. Makowski, and A. P. Wierzbicki, “Hierarchical reference approach to multicriteria analysis of discrete alternatives”, in CSM’06: 20th Worksh. Method. Tools Compl. Syst. Model. Integr. Policy Asses., Laxenburg, Austria, 2006.
  • [6] J. Granat and A. P. Wierzbicki, “Objective classification of empirical probability distributions and the issue of event detection” , in 23rd IFIP TC 7 Conf. Syst. Model. Optim., Cracow, Poland, 2007.
  • [7] S. Greco, B. Matarazzo, and R. Slowinski, “Rough sets theory for multicriteria decision analysis”, Eur. J. Oper. Res., vol. 129, no. 1, pp. 1–47, 2001.
  • [8] W. Heisenberg, “¨Uber den anschaulichen Inhalt der quantentheoretischen Kinematik und Mechanik”, Zeitschrift für Physik, vol. 43, pp. 172–198, 1927 (in Germany).
  • [9] H. S. Jensen, L. M. Richter, and M. T. Vendelø, The Evolution of Scientific Knowledge. Cheltenham: Edward Elgar, 2003.
  • [10] R. Keeney, Value Focused Thinking, a Path to Creative Decision Making. Cambridge: Harvard University Press, 1992.
  • [11] R. Keeney and H. Raiffa, Decisions with Multiple Objectives: Preferences and Value Tradeoffs. New York: Wiley, 1976.
  • [12] M. M. Kostreva, W. Ogryczak, and A. Wierzbicki, “Equitable aggregations and multiple criteria analysis”, Eur. J. Oper. Res., vol. 158, pp. 362–377, 2004.
  • [13] B. Latour, Science in Action. Milton Keynes: Open University Press, 1987.
  • [14] L. Lessig, Free Culture: The Nature and Future of Creativity. London: Penguin Books, 2004.
  • [15] K. Miettinen, Nonlinear Multiobjective Optimization. Boston: Kluwer, 1999.
  • [16] W. Ogryczak, “On multicriteria optimization with fair aggregation of individual achievements”, in CSM’06: 20th Worksh. Method. Tools Compl. Syst. Model. Integr. Policy Asses., Laxemburg, Austria, 2006.
  • [17] W. Ogryczak and A. Ruszczyński, “On consistence of stochastic dominance and mean-semideviation models”, Math. Program., vol. 89, pp. 217–232, 2001.
  • [18] Z. Pawlak, Rough Sets – Theoretical Aspects of Reasoning about Data. Dordrecht: Kluwer, 1991.
  • [19] K. R. Popper, Objective Knowledge. Oxford: Oxford University Press, 1972.
  • [20] W. V. Quine, “Two dogmas of empiricism”, in Philosophy of Mathematics, P. Benacerraf and H. Putnam. Englewood Cliffs: Prentice-Hall, 1953.
  • [21] J. Rawls, A Theory of Justice. Cambridge: Belknap Press, 1971.
  • [22] T. Saaty, Decision Making for Leaders: The Analytical Hierarchy Process for Decisions in a Complex World. Belmont: Lifetime Learning Publ., 1982.
  • [23] J. Tian, A. P. Wierzbicki, H. Ren, and Y. Nakamori, “A study on knowledge creation support in a Japanese Research Institute”, in Proceeding of First International Conference on Knowledge Science, Engineering and Management KSEM’06. Berlin-Heidelberg: Springer Verlag, 2006, pp. 405–417.
  • [24] A. P.Wierzbicki, “On the completeness and constructiveness of parametric characterizations to vector optimization problems”, OR Spektrum, vol. 8, pp. 73–87, 1986.
  • [25] A. P. Wierzbicki, “Technology and change: the role of technology in knowledge civilization”, in 1th World Congr. IFSR, Kobe, Japan, 2005.
  • [26] A. P. Wierzbicki, M. Makowski, and J. Wessels, Model-Based Decision Support Methodology with Environmental Applications. Dordrecht: Kluwer, 2000.
  • [27] A. P. Wierzbicki and Y. Nakamori, Creative Space: Models of Creative Processes for the Knowledge Civilization Age. Berlin-Heidelberg: Springer Verlag, 2006.
  • [28] A. P. Wierzbicki and Y. Nakamori, Eds., Creative Environments: Creativity Support for the Knowledge Civilization Age. Berlin-Heidelberg: Springer Verlag, 2007.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BATA-0001-0034
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