Application of Fuzzy Modelling to Predict Construction Projects Cash Flow

Authors

  • Sayed Mohammad Amin Tabei
    Affiliation
    Department of Financial Engineering, University of Economic Science, Tehran, Iran
  • Morteza Bagherpour
    Affiliation
    Department of Industrial Engineering, Iran University of Science and Technology
  • Amin Mahmoudi
    Affiliation
    Department of Industrial Engineering, Shiraz Branch, Azad University, Shiraz, Iran
https://doi.org/10.3311/PPci.13402

Abstract

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.

Keywords:

cash flow, fuzzy sets, predict cash flow, project management, construction projects

Citation data from Crossref and Scopus

Published Online

2019-03-19

How to Cite

Tabei, S. M. A., Bagherpour, M., Mahmoudi, A. “Application of Fuzzy Modelling to Predict Construction Projects Cash Flow”, Periodica Polytechnica Civil Engineering, 63(2), pp. 647–659, 2019. https://doi.org/10.3311/PPci.13402

Issue

Section

Technical Notes