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Improvement of Pair-wise Comparison Methods Based on Graph Theory Concepts

The paper briefly summarizes the currently available results of recent research on improvement of decision support methods, based on pair-wise comparisons of alternatives. Pair-wise comparison structures (especially, incomplete ones) can be easily represented by non-directed incidence graphs. It turns out that smaller-diameter quasi-regular graphs ensure higher credibility and consistency of expert session results, and maintain stability of preference structures. Particular pair-wise comparison patterns, both taking and not taking the rough ranking of alternatives into account, allow expert session organizers to significantly reduce the minimum required number of pair-wise comparisons, especially on large numbers of alternatives, without compromising the quality of expert data and credibility of expert session results. Following these patterns also allows us to reduce the computational complexity of pair-wise comparison-based decision support methods. Improved pair-wise-comparison-based decision support methods are widely applicable to decision-making problems in weakly-structured subject domains, calling for expert estimation.