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Abstract
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| he additive multi-attribute utility model is widely used in multicrite- ria decision-making. However, it is often not easy to elicit precise values for the scaling weights representing the relative importance of criteria. In a group deci- sion-making context a very widespread approach is to derive incomplete infor- mation, such as weight intervals or ordinal information rather than precise weights from a negotiation process. Different approaches have been proposed to deal with such situations. We advance two approaches based on dominance measures accounting for imprecise weights and compare them with other exist- ing approaches using Monte Carlo simulation. | |
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International
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Si |
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Book Edition
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0 |
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Book Publishing
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Springer |
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ISBN
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978-3-642-04427-4 |
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Series
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Lecture Notes in Artificial Intelligence |
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Book title
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Algorithmic Decision Theory |
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From page
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328 |
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To page
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339 |