Testing the Form of a Decision-Maker's Multiattribute Value Function Based on Pairwise Preference Information

In many cases, it may be difficult to obtain explicit information on criteria weights for multicriteria decision analysis. Usually, however, at least the relevant criteria can be assumed to be known, even if their weights are not. In addition, complete or incomplete rank order of these criteria can be known, and it may be possible to obtain estimates for at least some of the value-function parameters. With some decision support tools, such as stochastic multicriteria acceptability analysis (SMAA), it is possible to use incomplete information. The main results of SMAA are the probabilities of certain alternative obtaining a given rank, given all the information available. These probabilities can be used for choosing the most recommendable alternative. However, recommendations are risky when the preference information is incomplete. In this study, the risks are studied through a simulation study based on a previous forestry decision problem with multiple criteria. (1) The probability that the best alternative is recommended and (2) the expected losses in the value of value function due to choosing the wrong alternative are modelled as a function of the characteristics of the true value function and the best alternative. The results show that the quality of decisions improves very quickly with improving information on weights. Determining at least the complete rank order of criteria is advisable, especially if the importances vary markedly among the criteria.

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An Additive Value Function Technique with a Fuzzy Outranking Relation for Dealing with Poor Intercriteria Preference Information

Readings in Multiple Criteria Decision Aid ◽

10.1007/978-3-642-75935-2_16 ◽

1990 ◽

pp. 351-382 ◽

Cited By ~ 7

Author(s):

Carlos A. Bana e Costa

Keyword(s):

Value Function ◽

Function Technique ◽

Preference Information ◽

Additive Value Function ◽

Outranking Relation

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The hierarchical SMAA-PROMETHEE method applied to assess the sustainability of European cities

Applied Intelligence ◽

10.1007/s10489-021-02384-5 ◽

2021 ◽

Author(s):

Salvatore Corrente ◽

Salvatore Greco ◽

Floriana Leonardi ◽

Roman Słowiński

Keyword(s):

Value Function ◽

Specific Information ◽

Economic Sustainability ◽

Preference Model ◽

Preference Information ◽

Promethee Ii ◽

Decision Aiding ◽

European Cities ◽

Single Instance ◽

Promethee Method

AbstractMeasuring the level of sustainability taking into account many contributing aspects is a challenge. In this paper, we apply a multiple criteria decision aiding framework, namely, the hierarchical-SMAA-PROMETHEE method, to assess the environmental, social, and economic sustainability of 20 European cities in the period going from 2012 to 2015. The application of the method is innovative for the following reasons: (i) it permits to study the sustainability of the mentioned cities not only comprehensively but also considering separately particular macro-criteria, providing in this way more specific information on their weak and strong points; (ii) the use of PROMETHEE and, in particular, of PROMETHEE II, avoids the compensation between different and heterogeneous criteria, that is arbitrarily assumed in value function aggregation models; finally, (iii) thanks to the application of the Stochastic Multicriteria Acceptability Analysis, the method provides more robust recommendations than a method based on a single instance of the considered preference model compatible with few preference information items provided by the Decision Maker.

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