Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 2006

Powiadomienia systemowe

Sesja wygasła!

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: dane niepewne

Sortuj według:

Ogranicz wyniki do:

Wykorzystanie danych niepewnych do wspomagania oceny projektu inwestycyjnego przedsiębiorstwa

Bach I., Kopczewski M.

Zarządzanie Przedsiębiorstwem

2006

Vol. 9, nr 1

2-7

Project driven manufacturing provides a way for rising of enterprise competitiveness. Because of risk associated a project profitability evaluation plays a pivotal role. Due to standard economic approach many different methods such as Rol, IRR, NPV, PPz, can be used in the course of decision making, hi general case however any evaluation provided differs for the same project depends on the methods applied, hi that context, the imprecise and/or incomplete data can be employed as to support the decision maker. The proposed method is based on fuzzy logic knowledge representation formulae. Illustrative example of optimal project investment selection is provided. In case considered a company is faced with fife alternative projects: A, B, C, D, and E. The money amount, which has been allocated for investment, being in company's disposition is not enough, however to undertake all of them. So, some projects have to be rejected. Therefore, the question considered is how to choose the right projects. To cope with such problem, the standard economic methods based on NPV and IR indices have been applied. Due to the NPV the projects selected were: E, C and B. The projects are listed along the preference order, i.e., NPV(E) > NPV(C) > NPV(B), where NPV(A) - the NPV index value for the project A. In case of IR index, however, the obtained order of projects was the following one: E, B, C, and D. Because of the differences observed, the selection process was continued taking into account some qualitative and imprecise data following from experience of a project investor, credibility of a performer, and so on. So, on the base of fuzzy reasoning the second evaluation has been undertaken. The obtained order of projects consists of: B, D, A and E. Finally, taking into account results of both quantitative and qualitative evaluations the following projects were selected: E, B and D. Moreover, among of the projects A and C (that could be also considered), the only project C not exceeding assumed limits was added to the selected set of projects. The proposed approach to include additional, qualitative and imprecise data in the course of project evaluation provides a chance to make sure about the final decision. In general case, however leads to more sophisticated pohoptimal problem of decision making.