Capital Budgeting of Independent Projects with Budget Limitation Under Intuitionistic Fuzziness

Abstract

Companies have to make the right investment moves at the right time in order to sustain their existence and growth. For this reason, it is a critical decision for companies to distribute the existing capital to which projects and to what extent. Investment alternatives can be classified into two groups as dependent and independent. In dependent investment projects, the decision of whether to invest in a project directly affects the investment decision of the other project. In independent projects, it is necessary to consider the budget constraint in accordance with the reality of life. No matter how big the companies mentioned are, it is impossible to talk about an endless source of investment. For this reason, present value analysis, which is one of the most common methods used when evaluating independent project investments, is discussed under intuitionistic fuzziness in this study. It is aimed to achieve the most realistic results by reflecting the ambiguity and vagueness in the thoughts of the decision makers. In addition, this study demonstrates the integrability of fuzzy sets into engineering economics analysis methods. With this study, the cash flow data has been fuzzified and alternatives with both equal and different expected lives have been formulated to provide maximum returns under a certain budget limit. In addition, the responses of different parameters to changes were measured with intuitionistic fuzzy sensitivity analysis.

Keywords

• Capital Budgeting
• Independent Projects
• Budget Limitation
• Intuitionistic Fuzzy Sets

References

1. Atanassov, K.T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems 20(1), 87-96.
2. Can, G.F. (2018). Intituionistic fuzzy TLX (IF-TLX): Implementation of intuitionistic fuzzy set theory for evaluating subjective workload. Journal of Turkish Operations Management 2(1), 79-90.
3. de Souza Sampaio Filho, A.C., Vellasco, M.M.B.R., & Tanscheit, R. (2018). Modified methods of capital budgeting under uncertainties: An approach based on fuzzy numbers and interval arithmetic. Communications in Computer and Information Science 853, 777-789.
4. Etemadi, S., Koosha, H. & Salari, M. (2018). A goal programming capital budgeting model under uncertainty in construction industry. Scientia Iranica 25(2), 841-851.
5. Sampaio Filho, A.C.D.S., Vellasco, M.M.B.R., & Tanscheit, R. (2018). A unified solution in fuzzy capital budgeting. Expert Systems with Applications 98, 27-42.
6. Schneider, J., & Kuchta, D. (2018). Fuzzy capital budgeting for projects characterized by step type fuzzy intervals. Journal of Multiple-Valued Logic and Soft Computing 30(4-6), 303-334.
7. Sergi, D., & Sari, I.U. (2021). Fuzzy Capital Budgeting Using Fermatean Fuzzy Sets. Advances in Intelligent Systems and Computing 1197 AISC, 448-456.
8. Sergi, D., Sari, I.U., & Senapati, T. (2022). Extension of capital budgeting techniques using interval-valued Fermatean fuzzy sets. Journal of Intelligent and Fuzzy Systems 42(1), 365-376.

9. Silva, A.F.d., Marins, F.A.S., Dias, E.X., & Miranda, R.d.C. (2018). Fuzzy Goal Programming applied to the process of capital budget in an economic environment under uncertainty. Gestão & Produção 25(1), 148-159.
10. Liu, Y.H., Jiang, I.M., & Tsai, M.I. (2017). Making capital budgeting decisions for project abandonment by fuzzy approach. Lecture Notes in Computer Science 10386 LNCS, 277-284.
11. Ucal Sari, I., & Kahraman, C. (2015). Interval Type-2 Fuzzy Capital Budgeting. International Journal of Fuzzy Systems 17(4), 635-646.
12. Xu, Z. (2007). Some similarity measures of intuitionistic fuzzy sets and their applications to multiple attribute decision making. Fuzzy Optimization and Decision Making 6(2), 109-121.
13. Zadeh, L.A. (1965). Fuzzy sets. Information and Control 8(3), 338-353.
14. Zaralı, F. (2021). Intuitionistic fuzzy green supplier selection and an application in the machine manufacturing sector. Journal of Turkish Operations Management 5(1), 676-687.