5 research outputs found
A paired-comparison approach for fusing preference orderings from rank-ordered agents
The problem of aggregating multi-agent preference orderings has received considerable attention in
many fields of research, such as multi-criteria decision aiding and social choice theory; nevertheless, the
case in which the agents’ importance is expressed in the form of a rank-ordering, instead of a set of
weights, has not been much debated. The aim of this article is to present a novel algorithm – denominated
as ‘‘Ordered Paired-Comparisons Algorithm’’ (OPCA), which addresses this decision-making problem
in a relatively simple and practical way. The OPCA is organized into three main phases: (i) turning multi-
agent preference orderings into sets of paired comparisons, (ii) synthesizing the paired-comparison
sets, and (iii) constructing a fused (or consensus) ordering. Particularly interesting is phase two, which
introduces a new aggregation process based on a priority sequence, obtained from the agents’ importance
rank-ordering. A detailed description of the new algorithm is supported by practical examples
An evidential reasoning based approach for decision making with partially ordered preference under uncertainty
In many cases, decision making is to order alternatives and select one or a few among the top of the ranking based on
decision makers’ preferences. Due to the complexity and
flexibility of reality, decision makers usually can only provide partially ordered preferences with certain belief degrees. In order to deal with this kind of decision making problem, we introduce in this paper the use a belief structure for representing the involved partially ordered preferences with belief degrees, then a preference combination approach based on evidential reasoning is proposed to combine the preferences from different decision makers. The final ranking of alternatives is generated based on a distance measure between pairs of preference relations. An illustrative example is provided to show the rationality of the proposed method