Basic Definitions
The field variously described as multicriteria decision making (MCDM) or multicriteria decision analysis or aid (MCDA) is that branch of operational research/management science (OR/MS) that deals with the explicit modeling of multiple conflicting goals or objectives in management decision making. Standard texts in OR/MS typically do include identification of objectives (often stated as plural) as a key step in the decision-making process, but the ensuing discussion appears to assume that such objectives are easily aggregated into a single measure of achievement which can formally be optimized. The field of MCDA, however, arose from a recognition that systematic and coherent treatment of multiple objectives requires structured decision support to ensure that all interests are kept in mind and that an informed balance is achieved. See, for example, the discussions and associated references in Chap. 2 of Belton and Stewart (2002) and Chap. 1 of Figueira et al. (2005).
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References and Further Reading
Belton V, Stewart TJ (2002) Multiple criteria decision analysis: an integrated approach. Kluwer, Boston
Belton V Stewart TJ (2010) Problem structuring and MCDA. In: Ehrgott M, Figueira JR, Greco S (eds) Trends in multiple criteria decision analysis, chapter 8. Springer, Berlin, pp 237–271
Dyer JS (2005) MAUT – multiattribute utility theory. In: Figueira J, Greco S, Ehrgott M (eds) Multiple criteria decision analysis – state of the art annotated surveys. International series in operations research and management science, vol 76, chapter 7. Springer, New York, pp 265–295
Figueira J, Greco S, Ehrgott M (eds) (2005) Multiple criteria decision analysis – state of the art annotated surveys. International series in operations research and management science, vol 76. Springer, New York
Gal T, Stewart TJ, Hanne T (eds) (1999) Multicriteria decision making: advances in MCDM models, algorithms, theory, and applications. Kluwer, Boston
Greco S, Matarazzo B, Słowiński R (2005) Decision rule approach. In: Figueira J, Greco S, Ehrgott M (eds) Multiple criteria decision analysis – state of the art annotated surveys. International series in operations research and management science, vol 76, chapter 13. Springer, New York, pp 507–561
Keeney RL (1992) Value-focused thinking: a path to creative decision making. Harvard University Press, Cambridge
Keeney RL, Raiffa H (1976) Decisions with multiple objectives. Wiley, New York
Lee SM, Olson DL (1999) Goal programming. In: Gal T, Stewart TJ, Hanne T (eds) Multicriteria decision making: advances in MCDM models, algorithms, theory, and applications, chapter 8. Kluwer, Boston
Miettinen K (1999) Nonlinear multiobjective optimization, International series in operations research and management science, vol 12. Kluwer, Dordrecht
Saaty TL (2005) The analytic hierarchy and analytic network processes for the measurement of intangible criteria and for decision-making. In: Figueira J, Greco S, Ehrgott M (eds) Multiple criteria decision analysis – state of the art annotated surveys. International series in operations research and management science, vol 76, chapter 9. Springer, New York, pp 345–407
Siskos Y, Grigoroudis E, Matsatsinis N (2005) MAUT – multiattribute utility theory. In: Figueira J, Greco S, Ehrgott M (eds) Multiple criteria decision analysis – state of the art annotated surveys. International series in operations research and management science, vol 76, chapter 8. Springer, New York, pp 299–343
Stewart TJ (2005) Dealing with uncertainties in MCDA. In: Figueira J, Greco S, Ehrgott M (eds) Multiple criteria decision analysis – state of the art annotated surveys. International series in operations research and management science, vol 76, chapter 11. Springer, New York, pp 445–470
Wierzbicki AP (1999) Reference point approaches. In: Gal T, Stewart TJ, Hanne T (eds) Multicriteria decision making: advances in MCDM models, algorithms, theory, and applications, chapter 9, Kluwer, Boston
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Stewart, T.J. (2011). Multicriteria Decision Analysis. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_384
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