Requalifying public buildings and utilities using a group decision support system

Abstract Public buildings and utilities are responsible for a significant share of energy consumption and other related CO2 emissions. There is therefore an acute need for energy requalification interventions. Unfortunately, municipalities are under tight budget constraints – but decisions have to be made. A new hybrid group decision support system has been proposed in a bid to provide them with firm, transparent support. The system is based on a combination of the analytic hierarchy process, the K-means algorithm, and the 0–1 knapsack model. The first two methods aim at sorting alternatives into ordered classes of importance. To help in this task, the Bezier curve-fitting approach is used to construct the preference functions of decision-makers based on reference points. Then, the knapsack model selects the alternatives from the generated classes while complying with the budget constraints. A case study carried out in an Italian municipality allowed us to verify the validity of our new method in a real setting, and to highlight the advantages of an automatic sorting procedure in practice.

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