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.