Date of Award

Summer 8-1-2014

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Applied Engineering and Technology Management

Abstract

Engineering economic analysis techniques are used to evaluate projects and make appropriate decision in capital budgeting. Conventional projects can be solved by the traditional methods such as the net present value (NPV) and internal rate of return (IRR) methods. These methods may not work in evaluating non-conventional projects. Kulakov and Kulakova (2012) have presented the generalized net present value (GNPV) method for such projects. They have illustrated the method with three examples: a project of 2-year life with multiple IRRs, a project of 2-year life without IRR, and a project of 3-year life with a unique real-valued IRR which is not the rate of return. The purpose of the present study was to test the validity and feasibility of the GNPV method in evaluating other non-conventional projects with longer life. The method was used to evaluate five scenarios or problems with up to 10-year life. First problem was a project for 5-year life with multiple IRRs. Second was a project for 7-year life with multiple real-valued IRRs, which were not the rate of return. Third was a project for 10-year life with a positive and a negative IRR meaning the positive value was the unique IRR. Fourth was a project for 7-year life with a salvage value and a unique IRR. Fifth was a staged expansion project for 10-year life with a unique IRR. It was concluded that the GNPV method worked in all the five cases considered. Advantages of the GNPV method were noticed in agreement with Kulakov and Kulakova (2012) that i) the minimum attractive rate of return (MARR) was not required to find a solution of the problem; ii) the internal (financing) rate may be different from the external (reinvestment) rate as happens in real world; and iii) internal and external rates are not iii necessarily required for solution, but are required for evaluation of the projects. One disadvantage was observed that the computational work in some cases may be overwhelming.

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