Analyzing project cash flow by a new interval type-2 fuzzy model with an application to construction industry

Reliable knowledge of project cash flow is essential for effective project management. Since the nature of project is uncertain and easily effected by different criteria, considering uncertainty has become a vital part of any effective project management approach. Cash, as one of the most important project resources, requires reliable management techniques. In this paper, a new interval type-2 fuzzy project cash flow analysis model based on interval type-2 fuzzy project scheduling is proposed to predict project cash flow in different periods of project life cycle. Despite using type-2 fuzzy sets in various practical problems, they are new to project management; thus, they are used in this paper to address the uncertainty and lack of sufficient knowledge in project activity durations and costs. In the first part, interval type-2 fuzzy project scheduling model is introduced, and then the forward and the backward passes are defined. In order to improve this part, a new flexible and controllable method of interval type-2 fuzzy ranking is introduced. In the second part, a model of cash flow assessment is proposed under an interval type-2 fuzzy environment. This model is able to calculate the minimum and the maximum cash distribution, cash flow of project in different periods and total direct cost of projects in addition to cash flow uncertainty. The presented model provides the manager with a comprehensive insight into the cash required in different stages of project and helps the managers to locate the periods with highest uncertainty. The model also uses the concept of alpha-levels to analyze different levels of risk of uncertainty. For the purpose of illustration, the proposed interval type-2 fuzzy model is used to generate cash flow of main activities of a real construction project in a developing country, and the results are presented. The results present high flexibility of model in expressing and considering uncertainty and vagueness, in addition to its high capability in the risk evaluation. Finally, the results of the case study are used to present the managerial implications.