Requalifying public buildings and utilities using a group decision support system

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.