Vojnotehnički Glasnik (Oct 2021)

Uncertainty modeling using intuitionistic fuzzy numbers

  • Vladimir R. Milovanović,
  • Aleksandar V. Aleksić,
  • Vlada S. Sokolović,
  • Marjan A. Milenkov

DOI
https://doi.org/10.5937/vojtehg69-33301
Journal volume & issue
Vol. 69, no. 4
pp. 905 – 929

Abstract

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Introduction/purpose: The paper discusses the selection of the most optimal supplier using the example of an unmanned aircraft when the decision maker has data of a qualitative nature. Problems that arise in practice in the selection of suppliers relate to the selection of adequate criteria as well as the way they are evaluated by the decision maker. One of the ways of assessing the criteria of a qualitative character is the usage of linguistic expressions, which gives decision makers the freedom to express their position and opinion through descriptive assessments. This method of assessment is not the most accurate and can introduce a certain amount of uncertainty for the decision maker. Methods: To solve the problem of uncertainty, the paper proposes a method of modeling data using intuitive fuzzy numbers. Intuitive fuzzy numbers are suitable for solving the problem of uncertainty in situations when it is necessary to review safety during the assessment. To rank suppliers, the ELECTRE method is used, which is adapted to intuitive fuzzy numbers (IF ELECTRE). The IF ELECTRE method was chosen because it clearly presents the potential of all suppliers, i.e. their advantages and disadvantages in relation to the required criteria. Results: Using IF ELECTRE, the final results provide a shape of mutual preference or indifference between suppliers. The ranking clearly shows the potential of all suppliers, which in a future procurement can serve as a reference for decision making. Conclusion: The contribution of this paper is reflected in the proposed model that can be used in practice to solve not only the problem of supplier selection, but also similar problems where the decision is made based on inaccurate data. Using these models seeks to reduce indecision and subjectivity in decision making.

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