Logistic regression for criteria weight elicitation in PROMETHEE-based ranking methods

For a PROMETHEE II method used to rank concurrent alternatives both preference functions and weights are required, and if the weights are unknown, they can be elicited by leveraging present or past partial rankings. If the known partial ranking is incorrect, the eliciting methods are ineffective. In this paper a logistic regression method for weight elicitation is proposed to tackle this scenario. An experiment is carried out to compare the logistic regression method performance against a state-of-the-art linear weight elicitation method, proving the validity of the proposed methodology.