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Construction project managers are always looking for methods for forecasting future projects and preventing of potential delays in the project. One of the most crucial requirements of construction project managers and financial planners is awareness of project cash flow and financial status. On the other hand, the unique properties of construction projects with uncertainties such as activity duration, the variability of resources, material costs and also ambiguity in the employer’s payments are factors that have an effect on the correct prediction of project cash flow. Hence, the project team should examine project cash flow under uncertainty environment. There are many approaches for considering uncertainty such as fuzzy sets, interval theory, rough and grey system. But the most well-known approach is fuzzy sets which has wide applications in engineering and management. Hence in this paper, we proposed a new method for forecasting project cash flow under fuzzy environment. Finally, the proposed method was applied on an “Engineering, Procurement and Construction” (EPC) project and it is demonstrated that the proposed model has a high performance in the prediction of project cash flow.

Primary immunodeficiency disease (PID) comprises a genetically heterogeneous group of disorders caused by defects in components of the immune system. PIDs affect different components of the innate and adaptive immune systems, including neutrophils, macrophages, dendritic cells, complement proteins, natural killer (NK) cells, and T-and B-lymphocytes. [1 2] This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

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Material requirement planning (MRP) has evolved from a simplistic representation in the 1980s to today's manufacturing resource planning (MRPII) and enterprise resource planning (ERP) systems in order to meet changing business demands. The persisting momentous drive for lowest costs and highest quality dictates that MRP is deployed in an optimal manner. Multi-objective linear programming (MOLP), which is used simultaneously to optimize decisions through trade-offs between two or more conflicting objectives, has not been reported in MRP-related literature. As an extension of work reported by Yenisey [1], where optimization of material flow in MRP had been presented, a fuzzy multi-objective linear programming (f-MOLP) model is used where two objectives, namely minimization of total cost and minimization of total time of MRP, are targeted. The objective is to find the optimum production rate for each end-product at each period in accordance with the objectives and related constraints. The proposed f-MOLP is solved for two sets of conditions consisting of symmetric and asymmetric cases. The corresponding results show that the proposed models can help manufacturers make better decisions when facing uncertainty about objective functions as well as the constraints set. Degrees of satisfaction demonstrate the applicability of the proposed approach in the context of MRP.

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