Integration of human factors in project uncertainty management, a decision support system based on fuzzy logic

Decision-making under uncertainty implies dealing with information about different choices and their consequences that is partial for the decision-maker. In front of uncertainty, either the decision can be postponed, waiting for complementary information or the decision can be only made on the available information, despite possible consequences on the decision. We propose a model to identify and structure needed information. Human factors are taken into consideration in this structure. Then, to process the collected information, we propose a Fuzzy Decision Support System (FDSS) which deals with uncertain information. In this approach, a sequence of decisions leads to a final choice, taking progressively into account new information whose role is to refine available information. Human representation and reasoning mode are imitated, respectively by fuzzy sets and fuzzy inference rules. We apply the proposed FDSS to a case study held on a ski resort. The results with this approach prove effective compared to those a naive decisional approach.