Decision Support by Interval SMART/SWING - Incorporating Imprecision in the SMART and SWING Methods

Interval judgments are a way of handling preferential and informational imprecision in multicriteria decision analysis (MCDA). In this article, we study the use of intervals in the simple multiattribute rating technique (SMART) and SWING weighting methods. We generalize the methods by allowing the reference attribute to be any attribute, not just the most or the least important one, and by allowing the decision maker to reply with intervals to the weight ratio questions to account for his/her judgmental imprecision. We also study the practical and procedural implications of using imprecision intervals in these methods. These include, for example, how to select the reference attribute to identify as many dominated alternatives as possible. Based on the results of a simulation study, we suggest guidelines for how to carry out the weighting process in practice. Computer support can be used to make the process visual and interactive. We describe the WINPRE software for interval SMART/SWING, preference assessment by imprecise ratio statements (PAIRS), and preference programming. The use of interval SMART/SWING is illustrated by a job selection example.

[1]  R. Hämäläinen,et al.  Preference programming through approximate ratio comparisons , 1995 .

[2]  Martin Weber,et al.  Behavioral influences on weight judgments in multiattribute decision making , 1993 .

[3]  J S Hammond,et al.  Even swaps: a rational method for making trade-offs. , 1998, Harvard business review.

[4]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[5]  Ami Arbel,et al.  Approximate articulation of preference and priority derivation , 1989 .

[6]  Raimo P. Hämäläinen,et al.  Decisionarium ‐ aiding decisions, negotiating and collecting opinions on the web , 2005 .

[7]  R. Hämäläinen,et al.  On the measurement of preferences in the analytic hierarchy process , 1997 .

[8]  Raimo P. Hämäläinen,et al.  Preference ratios in multiattribute evaluation (PRIME)-elicitation and decision procedures under incomplete information , 2001, IEEE Trans. Syst. Man Cybern. Part A.

[9]  T. Stewart A CRITICAL SURVEY ON THE STATUS OF MULTIPLE CRITERIA DECISION MAKING THEORY AND PRACTICE , 1992 .

[10]  C. C. Waid,et al.  An Experimental Comparison of Different Approaches to Determining Weights in Additive Utility Models , 1982 .

[11]  Luis G. Vargas,et al.  Preference simulation and preference programming: robustness issues in priority derivation , 1993 .

[12]  Theodor J. Stewart,et al.  Multiple criteria decision analysis - an integrated approach , 2001 .

[13]  W. Edwards,et al.  Decision Analysis and Behavioral Research , 1986 .

[14]  Raimo P. Hämäläinen,et al.  On the convergence of multiattribute weighting methods , 2001, Eur. J. Oper. Res..

[15]  Ralph L. Keeney,et al.  Value-Focused Thinking: A Path to Creative Decisionmaking , 1992 .

[16]  Ralph L. Keeney,et al.  Book Reviews : Scientific Opportunities and Public Needs: Improv ing Priority Setting and Public Input at the National Institutes of Health. Institute of Medicine. Washington, DC: National Academy Press, 1998, 136 pages, $26.00 , 1998 .

[17]  Ralph L. Keeney,et al.  Decisions with multiple objectives: preferences and value tradeoffs , 1976 .

[18]  Hans Vrolijk,et al.  Behavioral and procedural consequences of structural variation in value trees , 2001, Eur. J. Oper. Res..

[19]  Martin Weber A Method of Multiattribute Decision Making with Incomplete Information , 1985 .

[20]  Eugene D. Hahn Decision Making with Uncertain Judgments: A Stochastic Formulation of the Analytic Hierarchy Process , 2003, Decis. Sci..

[21]  Preference Programming , 2003 .

[22]  Andrew P. Sage,et al.  ARIADNE: A knowledge-based interactive system for planning and decision support , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[23]  Ward Edwards,et al.  How to Use Multiattribute Utility Measurement for Social Decisionmaking , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[24]  R. Hämäläinen Decisionarium-aiding decisions, negotiating and collecting opinions on the web: DECISIONARIUM-AIDING DECISIONS , 2003 .

[25]  T. Saaty Highlights and critical points in the theory and application of the Analytic Hierarchy Process , 1994 .

[26]  Raimo P. Hämäläinen,et al.  Preference Assessment by Imprecise Ratio Statements , 1992, Oper. Res..

[27]  Thomas S. Wallsten,et al.  Measuring Vague Uncertainties and Understanding Their Use in Decision Making , 1990 .

[28]  Kwangtae Park,et al.  Extended methods for identifying dominance and potential optimality in multi-criteria analysis with imprecise information , 2001, Eur. J. Oper. Res..

[29]  Simon French,et al.  Uncertainty and Imprecision: Modelling and Analysis , 1995 .

[30]  Andrew P. Sage,et al.  A model of multiattribute decisionmaking and trade-off weight determination under uncertainty , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[31]  Ahti Salo,et al.  PRIME Decisions: An Interactive Tool for Value Tree Analysis , 2001 .

[32]  A. Stam,et al.  Stochastic Judgments in the AHP: The Measurement of Rank Reversal Probabilities , 1997 .

[33]  Martin Weber Decision Making with Incomplete Information , 1987 .

[34]  Soung Hie Kim,et al.  Establishing dominance and potential optimality in multi-criteria analysis with imprecise weight and value , 2001, Comput. Oper. Res..

[35]  Luis G. Vargas,et al.  Uncertainty and rank order in the analytic hierarchy process , 1987 .

[36]  R. L. Keeney,et al.  Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.