Group Decisions in Interval AHP Based on Interval Regression Analysis

For encouraging communication in a group decision making, this paper proposes methods to aggregate individual preferences. The individual preferences are denoted as the interval priority weights of alternatives by Interval Analytic Hierarchy Process (Interval AHP). It is proposed to handle subjective judgments since the induced results are intervals reflecting uncertainty of given information. When each decision maker gives the judgments on alternatives, the priority weights of alternatives are obtained. In the sense of reducing communication barriers, such information helps group members to realize their own preferences and the others’ opinions. Then, they are aggregated based on the concept of the interval regression analysis with interval output data, where two inclusion relations between the estimations and the observations are assumed. From the possibility view, the least upper approximation model is determined so as to include all observations. While, from the necessity view, the greatest lower approximation model is determined so as to be included in all observations. The former possible aggregations are acceptable for each group member and the latter necessary ones are useful for the supervisor at the upper level of decision making.

[1]  Ernest H. Forman,et al.  Group decision support with the Analytic Hierarchy Process , 1992, Decis. Support Syst..

[2]  Patrick T. Harker,et al.  The Analytic hierarchy process : applications and studies , 1989 .

[3]  Gerardine DeSanctis,et al.  A foundation for the study of group decision support systems , 1987 .

[4]  R. Ramanathan,et al.  Group preference aggregation methods employed in AHP: An evaluation and an intrinsic process for deriving members' weightages , 1994 .

[5]  Hideo Tanaka,et al.  Interval priorities in AHP by interval regression analysis , 2004, Eur. J. Oper. Res..

[6]  Tomoe Entani,et al.  Management of Ignorance by Interval Probability , 2007, 2007 IEEE International Fuzzy Systems Conference.

[7]  Thomas L. Saaty,et al.  Group Decision Making and the AHP , 1989 .

[8]  Luis M. de Campos,et al.  Probability Intervals: a Tool for uncertain Reasoning , 1994, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[9]  Hideo Tanaka,et al.  Possibilistic Data Analysis for Operations Research , 1999 .

[10]  Kirti Peniwati,et al.  Aggregating individual judgments and priorities with the analytic hierarchy process , 1998, Eur. J. Oper. Res..

[11]  Tomoe Entani,et al.  Interval AHP for Group of Decision Makers , 2009, IFSA/EUSFLAT Conf..

[12]  José María Moreno-Jiménez,et al.  A note on AHP group consistency for the row geometric mean priorization procedure , 2004, Eur. J. Oper. Res..

[13]  Ahti Salo,et al.  Interactive decision aiding for group decision support , 1995 .

[14]  Yutaka Maeda,et al.  Non-additive measures by interval probability functions , 2004, Inf. Sci..

[15]  Hideo Tanaka,et al.  Interval Evaluations in the Analytic Hierarchy Process By Possibility Analysis , 2001, Comput. Intell..

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

[17]  J. Barzilai,et al.  Ahp Rank Reversal, Normalization and Aggregation Rules , 1994 .