Decision criteria with partial information

Puerto, Justo; Mármol, Amparo M.; Fernández, Francisco R.

doi:10.1111/j.1475-3995.2000.tb00184.x

Cited by 37 publications

(19 citation statements)

References 11 publications

(14 reference statements)

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“…Other approaches to find the extreme points of S W have also been presented (Carrizosa et al, 1995;Mármol et al, 1998;Puerto et al, 2000;Mármol et al, 2002;Ahn, 2015).…”

Section: Ranking Candidates With Constraints On Rank Position Importancementioning

confidence: 99%

Aggregation of ranked votes considering different relative gaps between rank positions

Ahn

2017

Journal of the Operational Research Society

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This paper considers ranked voting systems to determine the rank order of candidates who compete for a limited number of positions. We show that the preferential voting problems based on the data envelopment analysis (DEA) (Wang et al, 2007) can be solved using the extreme points of constraints on rank position importance incorporated in the formulation. This is basically due to the fact that the so-called inverse positive property of the constraints makes it possible to easily find their extreme points. Further, we emphasize that this finding is not restricted to Wang et al's two linear models, but is also applicable to other DEA-based preferential voting problems, which include the constraints accounting for different relative gaps between rank positions.

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“…Other approaches to find the extreme points of S W have also been presented (Carrizosa et al, 1995;Mármol et al, 1998;Puerto et al, 2000;Mármol et al, 2002;Ahn, 2015).…”

Section: Ranking Candidates With Constraints On Rank Position Importancementioning

confidence: 99%

Aggregation of ranked votes considering different relative gaps between rank positions

Ahn

2017

Journal of the Operational Research Society

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“…For instance, in a DMM is proposed, which derives a global dominance intensity index to rank alternatives on the basis that rank the alternatives according to them. The performance of this method was compared in with other existing approaches (surrogate weighting methods, which select a weight vector from a set of admissible weights to represent the set (Stillwell et al, 1981); modified classical decision rules (Salo and Hamalainen, 2001;Puerto et al, 2000), and the DMM proposed in (Ahn and Park, 2008)), where ordinal information represents imprecision concerning weights.…”

Section: Deriving a Ranking Of Alternatives For Each Dmmentioning

confidence: 99%

Veto Values in Group Decision Making within MAUT - Aggregating Complete Rankings Derived from Dominance Intensity Measures

Jiménez-Martín

Sabio

Mateos

2015

Proceedings of the International Conference on Operations Research and Enterprise Systems

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Abstract:We consider a group decision-making problem within multi-attribute utility theory, in which the relative im portance of decision makers (DMs) is known and their preferences are represented by means of an additive function. We allow DMs to provide veto values for the attribute under consideration and build veto and adjust functions that are incorporated into the additive model. Veto functions check whether alternative performances are within the respective veto intervals, making the overall utility of the alternative equal to 0, whereas adjust functions reduce the utilty of the alternative performance to match the preferences of other DMs. Dominance measuring methods are used to account for imprecise information in the decision-making scenario and to de rive a ranking of alternatives for each DM. Specifically, ordinal information about the relative importance of criteria is provided by each DM. Finally, an extension of Kemeny's method is used to aggregate the alternative rankings from the DMs accounting for their relative importance.price, the location, the size or the age. One of the two might rule out any house smaller than 40m 2 , re gardless of house price, location and age, whereas the other might rule out any smaller than 60 m 2 . There fore, in this group decision-making scenario, a pos sible veto range would be [0,40], ruling out the pur chase of any house smaller than 40m 2 , and a possible adjust range would be (40,60], decreasing the utility of the respective house to account for the DM veto values.The veto concept has been variously considered as a real-world approach for representing the lim its of DM preferences in the literature.To establish these preferences the veto threshold is represented as a quantifiable measure, which becomes an important tool in multicriteria and group decision-making.

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“…The use of absolute dominance values is exemplified by the modification of four classical decision rules to encompass an imprecise decision context concerning weights and component values/utilities [22,26]: the maximax, in which each alternative is rated on the basis of its maximum guaranteed value; the maximin, based on its minimum guaranteed value; the minimax regret rule, based on the maximum loss of value with respect to a better alternative; and the central value rule, based on the midpoint of the range of possible performances.…”

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confidence: 99%

Dominance measuring methods for the selection of cleaning services in a European underground transportation company

2016

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Abstract. Dominance measuring methods are a recent approach for dealing with complex decisionmaking problems with imprecise, incomplete or partial information within multi-attribute value/utility theory. These methods compute pairwise dominance values and exploit the information included in the dominance matrix in different ways to derive measures of dominance intensity to rank the alternatives under consideration. We review dominance measuring methods proposed in the literature, describing how their possible drawbacks have been progressively overcome, and comparing their performance with other existing approaches, like surrogate weighting methods, the adaptation of classical decision rules to encompass an imprecise decision context, SMAA or Sarabando and Dias' method. An example of the selection of cleaning services in a European underground transportation company is used to illustrate dominance measuring methods in a real complex decision-making problem.Mathematics Subject Classification. 91B06, 91B16.

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Decision criteria with partial information

Cited by 37 publications

References 11 publications

Aggregation of ranked votes considering different relative gaps between rank positions

Aggregation of ranked votes considering different relative gaps between rank positions

Veto Values in Group Decision Making within MAUT - Aggregating Complete Rankings Derived from Dominance Intensity Measures

Dominance measuring methods for the selection of cleaning services in a European underground transportation company

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