Investment projects evaluation in a fuzzy environment using the simplified WISP method

  • Dragisa Stanujkic Tehnical Faculty in Bor
  • Aleksandra Fedajev
  • Marcos Santos
Keywords: MCDM, fuzzy,, triangular fuzzy numbers, Simplified WISP, investment projects

Abstract


This paper examines the importance of investment activity for companies and the challenges they face when evaluating investment projects in a fuzzy environment, that is when decisions have to be made based on some predictions and uncertain or imprecise data. The study focuses on the usage of a new extension of the Simplified WISP (Weighted Sum Product) method, which allows the use of triangular fuzzy numbers, as a tool for evaluating investment projects and minimizing the risk associated with such decisions. Investment projects were evaluated based on the following criteria: Net Present Value, Internal Rate of Return, Profitability Index, Payback Period, and Risk of project failure. The proposed extension of the Simplified WISP method can be used to solve other complex decision problems associated with predictions and uncertainties.The paper highlights the benefits of using this MCDM technique in investment project evaluation and the potential to improve decision-making processes. The study also discusses the challenges associated with applying MCDM techniques in a fuzzy environment and proposes solutions to overcome them. It also provides valuable insights for academics, practitioners, and policymakers interested in investment evaluation and decision-making processes.

References

Atanassov, K.T. (1986). Intuitionistic fuzzy sets. Fuzzy sets and Systems, 20 (1), 87-96.

Bhandari, S.B. (1989). Discounted payback period - A viable complement to net present value for projects with conventional cash flows. The Journal of Cost Analysis, 7 (1), 43-53.

Brans, J.P. (1982). Decision engineering. Development of decision support instruments. PROMETHEE method. In: Nadeau, R., Landry, M. (Eds.), Decision support: Nature, Instruments and Future Perspectives. Presses de l´Université Laval, Quebec, Canada, pp. 183-214. ( In French)

Chen, S.J., & Hwang, C.L. (1992). Fuzzy multiple attribute decision making methods: Methods and Applications. Berlin Heidelberg, Springer.

Cheng, C.B. (2004). Group opinion aggregation based on a grading process: A method for constructing triangular fuzzy numbers. Computers & Mathematics with Applications, 48 (10-11), 1619-1632.

Dai, H., Li, N., Wang, Y., & Zhao, X. (2022). The Analysis of Three Main Investment Criteria: NPV IRR and Payback Period. In 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) (pp. 185-189). Atlantis Press.

Dimova, L., Sevastianov, P., & Sevastianov, D. (2006). MCDM in a fuzzy setting: Investment projects assessment application. International Journal of Production Economics, 100 (1), 10-29.

Hublin, A., Schneider, D.R., & Džodan, J. (2014). Utilization of biogas produced by anaerobic digestion of agro-industrial waste: Energy, economic and environmental effects. Waste management & research, 32 (7), 626-633.

Hwang, C.L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple Attribute Decision Making. Springer, Berlin, Heidelberg, 58-191.

Ivanov, B., & Stanujkic, D. (2022). Evaluation of electric vehicles using the Simplified WISP method. In Proc. of the International Scientific Conference - UNITECH 2022, November 18-19, 2022, Gabrovo, Bulgaria.

Keshavarz Ghorabaee, M., Zavadskas, E.K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of Evaluation Based on Distance from Average Solution (EDAS). Informatica 26 (3), 435–451.

Kilic, M., & Kaya, İ. (2015). Investment project evaluation by a decision making methodology based on type-2 fuzzy sets. Applied Soft Computing, 27, 399-410.

Kirmizi, M., Karakas, S., & Uçar, H. (2023). Selecting the Optimal Naval Ship Drainage System Design Alternative Based on Integer Linear Programming, TOPSIS, and Simple WISP Methods. Journal of Ship Production and Design, 39 (2), 63-74.

Kose, F., Aksoy, M. H., & Ozgoren, M. (2014). An assessment of wind energy potential to meet electricity demand and economic feasibility in Konya, Turkey. International Journal of Green Energy, 11(6), 559-576.

Liou, T.S., & Wang, M.J.J. (1992). Ranking fuzzy numbers with integral value. Fuzzy sets and systems, 50 (3), 247-255.

Opricovic, S., & Tzeng, G. H. (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty. Fuzziness and Knowledge-Based Systems, 11 (5), 635-652.

Popovic, G., Stanujkic, D., & Stojanovic, S. (2012). Investment project selection by applying COPRAS method and imprecise data. Serbian Journal of Management, 7 (2), 257-269.

Rudnik, K., Bocewicz, G., Kucińska-Landwójtowicz, A., & Czabak-Górska, I.D. (2021). Ordered fuzzy WASPAS method for selection of improvement projects. Expert Systems with Applications, 169, 114471.

Saaty, T.L. (1978). Modeling unstructured decision problems – the theory of analytical hierarchies. Mathematics and Computers in Simulation, 20 (3), 147–158.

Smarandache, F. (1998). Neutrosophy Probability Set and Logic. American Research Press, Rehoboth.

Smarandache, F. (1999). A Unifying Field in Logics. Neutrosophy: Neutrosophic Probability, Set and Logic. American Research Press, Rehoboth.

Stanujkic, D. (2022). Development of the simple WISP method and is extensions. In Proc. of the XVIII International May Conference on Strategic Management - IMCSM22, 28 May 2022, Bor, Serbia.

Stanujkic, D., Karabasevic, D. & Saracevic, M. (2022). An adaptation of the simple WISP method and its testing by using Python. In Proc. of the 1th International conference Contemporary advancement in science and technology - COAST 2022, May 26-29, 2022, Herceg Novi, Montenegro.

Stanujkic, D., Popovic, G., Karabasevic, D., Meidute-Kavaliauskiene, I., & Ulutaş, A. (2023). An Integrated Simple Weighted Sum Product Method - WISP. IEEE Transactions on Engineering Management, 70(5), 1933-1944.

Stanujkic, D., Zavadskas, E. K., Karabasevic, D., Turskis, Z., & Keršulienė, V. (2017). New group decision-making ARCAS approach based on the integration of the SWARA and the ARAS methods adapted for negotiations. Journal of Business Economics and Management, 18 (4), 599-618.

Turksen, I. B. (1986). Interval valued fuzzy sets based on normal forms. Fuzzy sets and systems, 20(2), 191-210.

Ulutaş, A., Stanujkic, D., Karabasevic, D., Popovic, G., & Novaković, S. (2022). Pallet truck selection with MEREC and WISP-S methods. Strategic Management-International Journal of Strategic Management and Decision Support Systems in Strategic Management, 27(4), 23-29.

Yazdani, M., Zarate, P., Zavadskas, E. K., & Turskis, Z. (2018). A Combined Compromise Solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(3), 2501-2519.

Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.

Zavadskas, E.K., Stanujkic, D., Turskis, Z., & Karabasevic, D. (2022). An intuitionistic extension of the simple WISP method. Entropy, 24 (2), 218-229.

Zavadskas, E.K., Turskis, Z., Antucheviciene, J., & Zakarevicius, A. (2012). Optimization of weighted aggregated sum product assessment. Elektronika ir elektrotechnika, 122(6), 3–6.

Published
2023/11/16
Section
Original Scientific Paper