Publicação
Simple procedures of choice in multicriteria problems without precise information about the alternatives’ values
| Resumo: | The additive model of multiattribute value (or utility) the ory is widely used in multicriteria choice problems. However, often it is not easy to obtain precise values for the scaling weights or the alterna tives’ value in each function. Several decision rules have been proposed to select an alternative under these circumstances, which require weak er information, such as ordinal information. We propose new decision rules a nd test them using Monte-Carlo simulation, considering that there exists ordinal information both on the scaling weights and on the alternati ves’ values. Results show the new rules constitute a good approximation. We provide guidelines about how to use these rules in a context of select ing a subset of the most promising alternatives, considering the contradi ctory objectives of keeping a low number of alternatives yet not excluding the best one. |
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| Autores principais: | Sarabando, Paula |
| Outros Autores: | Dias, Luís |
| Assunto: | Multi-Criteria Decision Analysis MAUT/MAVT Imprecise/ incom- plete/ partial information Ordinal information Simulat ion |
| Ano: | 2009 |
| País: | Portugal |
| Tipo de documento: | relatório |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Viseu |
| Idioma: | inglês |
| Origem: | Repositório Científico do Instituto Politécnico de Viseu |
| Resumo: | The additive model of multiattribute value (or utility) the ory is widely used in multicriteria choice problems. However, often it is not easy to obtain precise values for the scaling weights or the alterna tives’ value in each function. Several decision rules have been proposed to select an alternative under these circumstances, which require weak er information, such as ordinal information. We propose new decision rules a nd test them using Monte-Carlo simulation, considering that there exists ordinal information both on the scaling weights and on the alternati ves’ values. Results show the new rules constitute a good approximation. We provide guidelines about how to use these rules in a context of select ing a subset of the most promising alternatives, considering the contradi ctory objectives of keeping a low number of alternatives yet not excluding the best one. |
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