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Similarity Measure of Lattice Ordered Multi-Fuzzy Soft Sets Based on Set Theoretic Approach and Its Application in Decision Making

Author

Listed:
  • Sabeena Begam S

    (Department of Mathematics, Alagappa University, Karaikudi 630004, India)

  • Vimala J

    (Department of Mathematics, Alagappa University, Karaikudi 630004, India)

  • Ganeshsree Selvachandran

    (Department of Actuarial Science and Applied Statistics, Faculty of Business and Information Science, UCSI University, Jalan Menara Gading, Cheras, Kuala Lumpur 56000, Malaysia)

  • Tran Thi Ngan

    (Faculty of Computer Science and Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 010000, Vietnam)

  • Rohit Sharma

    (Department of Electronics & Communication Engineering, SRM Institute of Science and Technology, Ghaziabad 201203, India)

Abstract

Many effective tools in fuzzy soft set theory have been proposed to handle various complicated problems in different fields of our real life, especially in decision making. Molodtsov’s soft set theory has been regarded as a newly emerging mathematical tool to deal with uncertainty and vagueness. Lattice ordered multi-fuzzy soft set ( L M F S S ) has been applied in forecasting process. However, similarity measure is not used in this application. In our research, similarity measure of L M F S S is proposed to calculate the similarity between two L M F S S s . Moreover, some of its properties are introduced and proved. Finally, an application of L M F S S in decision making using similarity measure is analysed.

Suggested Citation

  • Sabeena Begam S & Vimala J & Ganeshsree Selvachandran & Tran Thi Ngan & Rohit Sharma, 2020. "Similarity Measure of Lattice Ordered Multi-Fuzzy Soft Sets Based on Set Theoretic Approach and Its Application in Decision Making," Mathematics, MDPI, vol. 8(8), pages 1-15, July.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:8:p:1255-:d:392950
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    References listed on IDEAS

    as
    1. Leo Egghe, 2010. "Good properties of similarity measures and their complementarity," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(10), pages 2151-2160, October.
    2. Pinaki Majumdar & S. K. Samanta, 2008. "Similarity Measure Of Soft Sets," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-12.
    3. Sabu Sebastian & T. V. Ramakrishnan, 2011. "Multi-fuzzy sets: An extension of fuzzy sets," Fuzzy Information and Engineering, Springer, vol. 3(1), pages 35-43, March.
    4. Leo Egghe, 2010. "Good properties of similarity measures and their complementarity," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(10), pages 2151-2160, October.
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    Cited by:

    1. Sabeena Begam, S. & Vimala, J., 2022. "Compositions on lattice ordered multi-fuzzy soft matrix and its simulated application in medical diagnosis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 555-563.

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