The Development of Decision Support System for Fuzzy Project Evaluation Models in Engineering Economy

• Main Author: 林耀楨
• Other Authors: 劉世仰
• Format: Others
• Language: zh-TW
• Published: 1997
• Online Access: http://ndltd.ncl.edu.tw/handle/47665160824924276028

碩士 === 義守大學 === 管理科學研究所 === 85 === 　　The resource allocation theory in engineering economy is one of project evaluation techniques. Currently, the most widely used methods in resource allocation theory are present worth method,annual worth method, future worth method, benefit/cost ratio method, and internal rate of return method, Theoretically, these methods provide decision analysts an objective standard for evaluating different mutually-exclusive projects. However, all these approaches possess the following two drawbacks: (1) The evaluation result will be single and determainistic. The decision analyst can not obtain more useful information from the result; (2)The required input data (e. g. cash flow and interest rate) for these approaches are also certain. In real-world applications, these input data are usually fuzzy and uncertain. 　　To overcome the above weaknesses, this research attempts to develop an integrated fuzzy project evaluation models using fuzzy set theory. Specifically, this research develops numerous fuzzy project evaluation models by applying triangular fuzzy numbers. This project will consist of five main modules: (1) Fuzzy present worth module － evaluate different projects in terms of fuzzy present worth; (2)Fuzzy annual worth module─evaluate different projects in terms of fuzzy annual worth; (3)Fuzzy fntual worth module─evaluate different projects in terms of fuzzy future worth; (4)Fuzzy benefit/cost ratio module─evaluate different projects in terms of fuzzy benefit/cost ratio values; and (5) Fuzzy internal rae of return module ─ evaluate different projects in terms of fuzzy internal rate of return. 　　This research will prove that traditional evaluation approaches are special cases of the proposed fuzzy approaches. In other words, the proposed approaches still function normally under both certain and fuzzy situations. For the validation purpose, large amount of examples will be employed for evaluating these five modules. For the ease of system development and large amount of computation of fuzzy operations, this system will be developed and implemented under MS ─ Windows environment using both Fuzzy and Visual Basic software packages.