A Decision Support System for the Selection of Insulating Material in Energy Retrofit of Industrial Buildings: A New Robust Ordinal Regression Approach

Abstract

The criteria for selecting insulating materials in the energy retrofitting of industrial buildings can often be conflicting, leading to a multicriteria decision-making problem. This is the first study to take an indirect elicitation approach to solving this selection problem, which is particularly applicable in the preliminary phases of negotiation with all of the decision-makers involved. We introduce a nonlinear indirect elicitation approach for PROMETHEE II that uses Bézier curves as nonlinear preference curves to fit the decision-maker's preferences, i.e., indifference and/or strict preferences for insulating materials that are taken as references. In our approach, no parameters need to be initially set, and thus, it has the advantage of setting both the preference curves on the criteria and the criteria weights when the decision-maker is not confident. The set of Bézier curves and criteria weights that best fits the preferences given by the decision-maker may thus be achieved and visualized, which provides managerial insights as it makes explicit the preference structure of the decision-maker. We use a case study to validate our proposal in a real setting and confirm that linear preference curves would have achieved less clear relations between the insulating materials used as references respect to Bèzier curves.