A project selection framework of DSS by Dempster-Shafer Theory under fuzziness

This paper exposits evolutionary MCDM techniques which integrates Dempster -Shafer Theory (DST) of evidence, quantificational evidence preference from different criteria based on belief function. In this paper, current researchers´ proposed method is able to preference rank a no. of alternative projects under uncertainty for project selection based on imperfect information coming out from more or less reliable and conflicting sources. Under fuzziness the integrated MCDM method uses possibility and belief function theory to take a decision based on imprecise and uncertain evaluations of quantitative and qualitative criteria. The derived ranking of alternative is based on DST related belief and plausibility measures.