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2013 | 5(65) | 14-33
Article title

Rank Ordering Criteria Weighting Methods – a Comparative Overview

Authors
Title variants
Languages of publication
EN
Abstracts
EN
Multicriteria decision making (MCDM) refers to screening, prioritizing, ranking or selecting the alternatives based on human judgment from among a finite set of ` alternatives in terms of the multiple usually conflicting criteria. A very significant role in MCDM models plays the weights of criteria which usually provide the information about the relative importance of the considered criteria. Several different methods are developed to take criteria priorities into account. The aim of the paper is a comparative overview on several rank ordering weights methods which are considered to convert the ordinal ranking of a number of criteria into numerical weights. Using ranks to elicit weights by some formulas is more reliable than just directly assigning weights to criteria because usually decision makers are more confident about the ranks of some criteria than their weights, and they can agree on ranks more easily. The great advantage of those methods is the fact that they rely only on ordinal information about attribute importance. They can be used for instance in situations of time pressure, quality nature of criteria, lack of knowledge, imprecise, incomplete information or partial information, decision maker’s limited attention and information processing capability. The equal weights, rank sum, rank exponent, rank reciprocal as well centroid weights technique are presented. These methods have been selected for their simplicity and effectiveness.
Year
Issue
Pages
14-33
Physical description
Contributors
  • Uniwersytet w białymstoku
References
  • Ahn B. S., Park K. S., 2008, Comparing Methods for Multiattribute Decision-making with Ordinal Weights, “Computers & Operations Research” 35 (5), 1660-1670.
  • Barron F. H., Barrett B. E., 1996a, The Efficacy of SMARTER: Simple Multiattribute Rating Technique Extended to Ranking, “Acta Psychologica” 93(1–3), 23–36.
  • Barron F., Barrett B. E., 1996b, Decision Quality Using Ranked Attribute Weights, Management Science 42, 1515-1523.
  • Barron F. H., 1992, Selecting a Best Multiattribute Alternative with Partial Information about Attribute Weights, Acta Psychologica 80, 91-103.
  • Belton V., Stewart T. J, 2002, Multiple Criteria Decision Analysis: An Integrated Approch, Kluwer, Dordrecht.
  • Borcherding K., Eppel T., von Winterfeldt D., 1991, Comparison of Weighting Judgments in Multiattribute Utility Measurement, “Manage Science” 37, 1603–1619.
  • Bottomley P. A., Doyle J. R., 2001, A Comparison of Three Weight Elicitation Methods: Good, Better, and Best, “Omega” 29, 553-560.
  • Choo E. U., Schoner B., Wedley W. C., 1999, Interpretation of Criteria Weights in Multicriteria Decision-making, “Computers & Industrial Engineering” 37, 527-541.
  • Diakoulaki D., Mavrotas G., Papayannakis L., 1995, Determining Objective Weights in Multiple Criteria Problems: The Critic Method, “Computers & Operations Research” 22, 763-770.
  • Doyle J. R., Green R. H., Bottomley P. A., 1997, Judging Relative Importance: Direct Rating and Point Allocation Are not Equivalent, “Organizational Behavior and Human Decision Processes” 70, 55-72.
  • Edwards W., 1977, How to Use Multiattribute Utility Analysis for Social Decision-making, IEEE Trans Syst Man Cybernet SMC-7 , 326–340.
  • Edwards W., Barron F. H., 1994, SMARTS and SMARTER: Improved Simple Methods for Multiattribute Utility Measurement, “Organizational Behavior and Human Decision Processes” 60, 306–325.
  • Fan Z. P., Ma J., Zhang Q., 2002, An Approach to Multiple Attribute Decision-making Based on Fuzzy Preference Information on Alternatives, “Fuzzy Sets and Systems” 131, 101-106.
  • Horsky D., Rao M. R., 1984, Estimation of Attribute Weights from Preference Comparisons, “Management Sciences” 30, 1801-822.
  • Hwang C. L., Yoon K., 1981, Multiple Attribute Decision-making: Methods and Applications, Springer, Berlin.
  • Jia J, Fischer G. W, Dyer J. S., 1998, Attribute Weighting Methods and Decision Quality in the Presence of Sampling Error: a Simulation Study, “Journal of Behavioral Decision Making” 11(2), 85–105.
  • Keeney R. L., Raiffa H., 1976, Decisions with Multiple Objectives: Preferences and Value Tradeoffs, Wiley, New York.
  • Kirkwood C. W., 1997, Strategic Decision-making: Multiobjective Decision Analysis with Spreadsheets, Duxbury Press, Belmont, CA.
  • Lootsma F. A., 1996, A Model for the Relative Importance of the Criteria in the Multiplicative AHP and SMART, “European Journal of Operational Research”, 94, 467-476.
  • Lootsma F. A., Bots, P. W. G., 1999, The Assignment of Scores for Output-based Research Funding, “Journal of Multi-Criteria Decision Analysis”, 8, 44-50.
  • Ma J., Fan Z. P., Huang L. H., 1999, A Subjective and Objective Integrated Approach to Determine Attribute Weights, “European Journal of Operational Research” 112, 397-404.
  • Maggino, F., Ruviglioni, E., 2011, Obtaining Weights: from Objective to Subjective Approaches in View of More Participative Methods in the Construction of Composite Indicators, Proceedings of new techniques and technologies for statistics, Eurostat, Brussels, Belgium.
  • Available from: http://epp.eurostat.ec. europa.eu/portal/page/portal/research_methodology/documents/POSTER_1A_OBTAINING_WEIGHTS_MAGGINO_RUVIGLIONI. pdf [Accessed 16 May 2012].
  • Noh J., Lee M. L., 2003, Application of Multiattribute Decision-making Methods for the Determination of Relative Significance Factor of Impact Categories, “Environmental Management” 31(5), 633–641.
  • Olson D. L., Dorai V. K., 1992, Implementation of the Centroid Method of Solymosi and Dompi, “European Journal of Operational Research” 60(1), 117–129.
  • Saaty T. L., 1980, The Analytical Hierarchy Process, McGraw-Hill, New York.
  • Solymosi T., Dombi J., 1986, A Method for Determining the Weights of Criteria: The Centralized Weights, “European Journal of Operational Research” 26.
  • Solymosi T., Dompi J., 1985, Method for Determining the Weights of Criteria: the Centralized Weights, “European Journal of Operational Research”, 26, 35-41.
  • Srivastava J., Connoly T, Beach L. R., 1995, Do Ranks Suffice? A Comparison of Alternative Weighting Approaches in Value Elicitation, “Organizational Behavior and Human Decision Processes” 63(1), 112–116.
  • Stillwell W. G., Seaver D. A., Edwards W., 1981, A Comparison of Weight Approximation Techniques in Multiattribute Utility Decision-Making, “Organizational Behavior and Human Performance”, 28, 62-77.
  • Takeda E., Cogger K. O., Yu P. L., 1987, Estimating Criterion Weights Using Eigenvectors: A Comparative Study, “European Journal of Operational Research” 29, 360-369.
  • Tzeng G.H, Chen T.Y, Wang J.C., (1998), A Weight Assessing Method with Habitual Domains. European Journal of Operational Research 110(2), 342–367.
  • Xu X., 2004, A Note on the Subjective and Objective Integrated Approach to Determine Attribute Weights, “European Journal of Operational Research” 156, 530-532.
  • Wang Y. M., Parkan C., 2006, A General Multiple Attribute Decision-making Approach for Integrating Subjective Preferences and Objective Information, “Fuzzy Sets and Systems” 157, 1333-1345.
  • Weber M., Borcherding K., 1993, Behavioral Influences on Weight Judgments in Multiattribute Decision-Making, “European Journal of Operational Research” 67(1), 1–12.
  • Wu Z., Chen Y., 2007,The Maximizing Deviation Method for Group Multiple Attribute Decision Making under Linguistic Environment, “Fuzzy Sets and Systems” 158 (14), 1608-1617.
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-318faf1b-bbdf-4ab6-b572-78389af89c35
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