Spreadsheet risk analysis using simulation
Simulation
Introduction to simulation and SLAM II (4th ed.)
Introduction to simulation and SLAM II (4th ed.)
Simulation Modeling and Analysis
Simulation Modeling and Analysis
An integrated decision support approach for project investors in risky and uncertain environments
Journal of Computational and Applied Mathematics
Mathematical and Computer Modelling: An International Journal
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Some information required for solving problems in engineering economy problems can be fairly well defined. Much required information is uncertain, such as the actual cash flows from revenues and costs, the salvage value of equipment, the interest rate or even the project life. Engineering economy problems with all deterministic inputs are actually special cases. Probability descriptions of input variables and Monte Carlo sampling together provide a practical method of finding the distribution of the desired output given the various random and deterministic input variables. This paper provides three examples that demonstrate how commonly available simulation software could be used in engineering economy problems. One example is demonstrated that generates the distribution future worth of an annual series of payments when there is uncertainty about the future earning power (interest rate) from year to year. Also, an example is demonstrated that models the uncertainty of interest rates and the uncertainty of project life in order to generate the NPV distribution of a project. Finally, an example is presented to show the use of simulation in comparing alternative investment opportunities under uncertainty. These examples can be used to demonstrate how risk is handled in an engineering economy course. The examples can also be used as additional applications in an industrial simulation course.