Rank inclusion in criteria hierarchies |
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| Affiliation: | 1. School of Business, East China University of Science and Technology, Meilong Road No. 130, Shanghai 200237, China;2. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China;3. School of Economics and Management, Beihang University, Xueyuan Road No. 37, Haidian District, Beijing 100191 China;1. Laboratory of Mathematical Ecology, A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow 119 017, Russia;2. Institute of Forest Science, Russian Academy of Sciences, Uspenskoe 143030, Russia |
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| Abstract: | This paper presents a method called Rank Inclusion in Criteria Hierarchies (RICH) for the analysis of incomplete preference information in hierarchical weighting models. In RICH, the decision maker is allowed to specify subsets of attributes which contain the most important attribute or, more generally, to associate a set of rankings with a given set of attributes. Such preference statements lead to possibly non-convex sets of feasible attribute weights, allowing decision recommendations to be obtained through the computation of dominance relations and decision rules. An illustrative example on the selection of a subcontractor is presented, and the computational properties of RICH are considered. |
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