Spatial multi-attribute decision making: An axiomatic incomplete preference information coverage model

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In addressing the spatial multi-attribute decision making with conflicting incomplete preference information, this study presents an axiomatic preference information coverage model, which can determine the group’s collective stance without distorting individual’s original spatial preferences. First, with a Preference Information (PI) set to encapsulate the incomplete spatial preference information, we extend existing additive spatial value function with a stochastic weight space to assign utilities to alternatives. Dominance relations among pairwise alternatives based on expected utility maximization inform the alternatives priority sequences. Within this context, a novel preference information measure is introduced, serving as the basis for defining the coverage degree associated with alternatives priority sequences relative to the PI. In alignment with the axiomatic foundations governing coverage degree and the principle of maximizing this metric, a dominant rule is formulated to dictate the hierarchy among alternatives priority sequences. The model’s applicability is demonstrated via a numerical example, followed by simulation analyses that probe the influence of different PIs on coverage degree.