Novel Bipolar Soft Rough-Set Approximations and Their Application in Solving Decision-Making Problems

다국어 초록 (Multilingual Abstract)

The rough set (RS) theory is a successful approach for studying the uncertainty in data. Incontrast, the bipolar soft sets (BSS) can deal with the uncertainty, as well as bipolarity ofthe data in many situations. In 2018, Karaaslan and C¸ agman proposed bipolar soft rough ˘sets (BSRSs), a hybridization of RS and BSS. However, certain shortcomings with BSRSviolate Pawlak’s RS theory. To overcome these shortcomings, the concept of the modifiedbipolar soft rough set (MBSRS) has been proposed in this study. Moreover, this idea hasbeen investigated through illustrative examples, where the important properties are inspecteddeeply. Furthermore, certain significant measures associated with MBSRS are also provided.
Finally, an application of the MBSRS to multi-attribute group decision-making (MAGDM)problems is proposed. In addition, among various alternatives, an algorithm for decisionmaking accompanied by a practical example is presented as the optimal alternative . A briefcomparative analysis of the proposed approach with some existing techniques is also providedto indicate the validity, flexibility, and superiority of the suggested MAGDM model.

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