An Extension of the ELECTRE III Method based on the 2-tuple Linguistic Representation Model for Dealing with Heterogeneous Information
Abstract
Multicriteria decision analysis (MCDA) is a problem-solving approach that helps to tackle complex decision-making problems. It involves analyzing a set of alternatives that are assessed based on a set of decision criteria by one or more decision-makers. These decision-makers use both subjective and objective judgments, which can be qualitative and/or quantitative. The goal of MCDA is to arrive at a decision that is fair, effective, and considers all relevant factors. Some MCDA methods lack mechanisms to consistently process heterogeneous information provided by the decision-maker and reduce it simplistically to numerical values to assess subjective criteria and thus obtain numerical results with low interpretability. This paper presents an extension of the ELECTRE III method that considers heterogeneous information provided by the decision-maker as input data in the decision criteria. The new proposal is based on the 2-tuple linguistic representation model, which allows for a flexible assessment structure in which the decision-maker can provide their preferences by applying diverse levels of information according to the nature and uncertainty of the decision criteria. It includes a new distance measure based on linguistic transformations appropriate for the MCDA outranking approach. Finally, the viability and pertinence of the proposed method are shown in a case to evaluate the environmental impact that can occur between the interactions of some industrial activities in a petrol station.
Keywords
Computing with Words, Heterogeneous Information, Linguistic Preferences, Multicriteria Decision Analysis, ELECTRE III