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Neutrosophic Hypersoft Matrix Theory: Its Definition, Operators, and Application in Decision-Making of Personnel Selection Problem

In: Neutrosophic Operational Research

Author

Listed:
  • Muhammad Saqlain

    (Lahore Garrison University, DHA Phase-VI, Sector C)

  • Muhammad Saeed

    (School of Mathematics, University of Management and Technology)

  • Rana Muhammad Zulqarnain

    (Northwest University Xi’an)

  • Sana Moin

    (Lahore Garrison University, DHA Phase-VI, Sector C)

Abstract

In the previous paper, the concept of TOPSIS for neutrosophic hypersoft sets was proposed to solve the decision-making problem, and it was used for finding best alternative routes (Saqlain et al.) However, the aggregate operators of the proposed algorithm have not been presented yet. To handle indeterminacy, vagueness, and hesitation, neutrosophic hypersoft set can be used. In this paper, we have firstly defined neutrosophic hypersoft matrix (NHSM) and their operators, i.e., sum, difference, product, AND, OR, NOT, and types of matrices; secondly, based on some of these NHSM operators, an algorithm is proposed, namely (NHSM algorithm), to solve multi-attributive multi-criteria decision problems (MAMCDP); and lastly results are compared with the algorithm proposed by Saqlain et al. It is concluded that a new proposed algorithm is efficient and simple for optimal choice selection to solve MAMCDP. In future, proposed operators and algorithm can be used to solve complex problems of decision-making in which multiple attribute and alternative-based selection is made involving multiple decision makers.

Suggested Citation

  • Muhammad Saqlain & Muhammad Saeed & Rana Muhammad Zulqarnain & Sana Moin, 2021. "Neutrosophic Hypersoft Matrix Theory: Its Definition, Operators, and Application in Decision-Making of Personnel Selection Problem," Springer Books, in: Florentin Smarandache & Mohamed Abdel-Basset (ed.), Neutrosophic Operational Research, pages 449-470, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-57197-9_21
    DOI: 10.1007/978-3-030-57197-9_21
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