Wykorzystanie danych niepewnych do wspomagania oceny projektu inwestycyjnego przedsiębiorstwa

• Autorzy: Bach I. , Kopczewski M.

Warianty tytułu

EN

An application of imprecise and/or incomplete data to support as of optimum investment project choice

• Konferencja: X jubileuszowa Konferencja "Komputerowo Zintegrowane Zarządzanie" (X; 15-17.01.2007; Zakopane, Polska)
• Języki publikacji: PL

Abstrakty

EN

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.

Słowa kluczowe

PL

analiza ekonomiczna; wnioskowanie rozmyte; projekt inwestycyjny; dane niepewne

• Wydawca: Polskie Towarzystwo Zarządzania Produkcją
• Czasopismo: Zarządzanie Przedsiębiorstwem
• Rocznik: 2006
• Tom: Vol. 9, nr 1
• Strony: 2--7
• Opis fizyczny: Bibliogr. 6 poz.

Twórcy

autor

Bach I.

autor

Kopczewski M.

• Politechnika Koszalińska, Wydział Elektroniki i Informatyki, Katedra Podstaw Informatyki i Zarządzania, ul. Śniadeckich 2, 75-453 Koszalin,

Bibliografia

• [1] Bednarski L., Borowiecki R., Duraj J., Kurtys E., Waśniewski T., Wersty B.: Analiza ekonomiczna przedsiębiorstwa, Wydawnictwo Akademii Ekonomicznej we Wrocławiu, Wrocław 1996.
• [2] Białko M.: Sztuczna inteligencja i elementy hybrydowych systemów ekspertowych, Wyd. Wydawnictwo Uczelniane Politechniki Koszalińskiej, Koszalin 2005.
• [3] Grabski R, Jadźwiński J.: Metody Bayesowskie, WKŁ, Warszawa 2001.
• [4] Krzemińska D.: Finanse Przedsiębiorstw, Wydawnictwo Wyższej Szkoły Bankowej, Toruń 2002.
• [5] Piegat A.: Modelowanie i sterowanie rozmyte, Akademicka Oficyna Wydawnicza EXIT, Warszawa 1999.
• [6] Sangajło R., Stronka D.: Zarządzanie finansami przedsiębiorstw, tom II, Wydawnictwo Wyższej Szkoły Komunikacji i Zarządzania, Poznań 2001.