Rosinger, Elemér E. Beyond preference information based multiple criteria decision making. (English) Zbl 0732.90044 Eur. J. Oper. Res. 53, No. 2, 217-227 (1991). Summary: The aim of the paper is twofold. First, it shows the increasing irrelevance of preference information, as the number of criteria becomes moderately large. This phenomenon can be called the principle of increasing irrelevance of preference information, in short, PIIPI. Secondly, a rather large class of interactive MCDM methods is presented, which are mainly based on the use of nonpreference information, processed by specially developed clustering algorithms. An initial, restricted version of these methods has previously been suggested by the author. Cited in 1 Document MSC: 90B50 Management decision making, including multiple objectives 91B08 Individual preferences Keywords:preference information; increasing irrelevance; clustering algorithms PDF BibTeX XML Cite \textit{E. E. Rosinger}, Eur. J. Oper. Res. 53, No. 2, 217--227 (1991; Zbl 0732.90044) Full Text: DOI OpenURL References: [1] Gershon, M.; Duckstein, L., An algorithm for choosing of a multiobjective technique, (), Paper presented at the · Zbl 0557.90097 [2] Gordon, A.D., Classification method for the exploratory analysis of multivariate date, (1981), Chapman and Hall London · Zbl 0507.62057 [3] Manin, Yu.I., Mathematics and physics, (1981), Birkhauser Boston, MD · Zbl 0472.00018 [4] Michalski, R.S.; Diday, E., A recent advance in data analysis. clustering objects into classes characterized by conjunctive concepts, () [5] Milligan, G.W.; Cooper, M.C., An examination of procedures for determining the number of clusters in a data set, Psychometrica, 50, 2, 159-179, (1985) [6] Rivett, P., The use of local-global mapping techniques in analysing multi criteria decision making, () [7] Rosenthal, R.E., Principles of multiobjective optimization, (1984), Naval Post-graduate School Monterey, CA [8] Rosinger, E.E., Aids for decision making with conflicting objectives, (), 275-315 · Zbl 0503.90055 [9] Rosinger, E.E., MCDM, a clustering technique approach, (), Kyoto, Japan [10] Roy, B., Partial preference analysis and decision aid; the fuzzy outranking relation concept, () [11] Roy, G.G., The use of multi-dimensional scaling in policy selection, Journal of the operational research society, 33, 239-245, (1982) [12] Späth, H., Cluster analysis algorithm for data reduction and classification of objects, (1980), Wiley New York [13] Wallenius, H., Optimizing macroeconomic policy: A review of approaches and applications, European journal of operational research, 10, 221-228, (1982) [14] Wallenius, J., Comparative evaluation of some interactive approaches to multicriterion optimization, Management science, 21, 1387-1397, (1975) · Zbl 0307.90084 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.