Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
R&D project evaluation model based on fuzzy set priority
ICC&IE Selected papers from the 22nd ICC&IE conference on Computers & industrial engineering
Fuzzy Sets and Systems
Transportation projects selection process using fuzzy sets theory
Fuzzy Sets and Systems - special issue on fuzzy sets in traffic and transport systems
Simulation with Arena
Capital budgeting techniques using discounted fuzzy versus probabilistic cash flows
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Intelligent information systems and applications
Using simulation software to solve engineering economy problems
Computers and Industrial Engineering - Special issue: Selected papers from the 25th international conference on computers & industrial engineering in New Orleans, Louisiana
Hi-index | 7.29 |
In project investment decisions, it is often assumed that estimated values of project parameters are certain and they would not deviate by the time. However, project parameters normally change during a life cycle of the project. Therefore, an existence of a deviation or gap between forecasted values and actual values is inevitable. Because of the uncertainty of the future, forecasting the true and exact values of project parameters is almost impossible. In this study, an integrated decision support approach based on simulation and fuzzy set theory is proposed for project investors in risky and uncertain environments. This approach determines the risk levels of the projects and helps investors to make investment decisions. In the scope of the study, a flowchart is presented to guide to decision maker in different situations of information uncertainty that belongs to project parameter values. Via this flowchart, the values of project parameters can be chosen depending on how they are determined (deterministic, stochastic or fuzzy) by project analyst. Besides, calculating and analyzing the project risk in all possible situations would be easier. Illustrative examples are given to demonstrate the application of this approach.