Tight upper bounds for the expected loss of lexicographic heuristics in binary multiattribute choice
Tight upper bounds for the expected loss of the DEBA (Deterministic-Elimination-By-Aspects) lexicographic selection heuristic are obtained for the case of an additive separable utility function with unknown non-negative, non-increasing attribute weights for numbers of alternatives and attributes as...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2008 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/21073 |
| Acceso en línea: | https://hdl.handle.net/2117/21073 |
| Access Level: | acceso abierto |
| Palabra clave: | Problem solving Decision-making Solució de problemes Decisió, Presa de Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi matemàtica |
| Sumario: | Tight upper bounds for the expected loss of the DEBA (Deterministic-Elimination-By-Aspects) lexicographic selection heuristic are obtained for the case of an additive separable utility function with unknown non-negative, non-increasing attribute weights for numbers of alternatives and attributes as large as 10 under two probabilistic models: one in which attributes are assumed to be independent Bernouilli random variables and another one with positive inter-attribute correlation. The upper bounds improve substantially previous bounds and extend significantly the cases in which a good performance of DEBA can be guaranteed under the assumed cognitive limitations. |
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