A group decision model for evaluating and selecting intelligent building systems under uncertainty

This paper presents a group decision model for evaluating and selecting intelligent building systems under uncertainty. Linguistic variables approximated by fuzzy numbers are used for dealing with the decision maker's subjective assessments. Pairwise comparison is adopted for reducing the cognitive burden of the decision maker in the evaluation process. A group decision model is developed for producing the performance index of available alternatives on which the overall ranking of alternatives can be obtained. As a result, effective decisions can be made. An example is presented for demonstrating the applicability of the group decision model.