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.
A paired-comparison approach for fusing preference orderings from rank-ordered agents / Franceschini, Fiorenzo; Maisano, DOMENICO AUGUSTO FRANCESCO; Mastrogiacomo, Luca. - In: INFORMATION FUSION. - ISSN 1566-2535. - STAMPA. - 26:(2015), pp. 84-95. [10.1016/j.inffus.2015.01.004]
A paired-comparison approach for fusing preference orderings from rank-ordered agents
FRANCESCHINI, FIORENZO;MAISANO, DOMENICO AUGUSTO FRANCESCO;MASTROGIACOMO, LUCA
2015
Abstract
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.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2606155
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