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M-polar fuzzy Muirhead mean aggregation operators with their decision-making application in telecommunication

algorithms-and-analysis-of-algorithms
optimization-theory-and-computation
theory-and-formal-methods

Abstract

An effective antenna design in the telecommunication domain performs a significant role by ensuring efficient reception and transmission of signals, reducing power loss, and providing wider coverage. The design of an antenna depends on multiple polar factors like radiation pattern, frequency range, environmental conditions, bandwidth, and size. Due to the involvement of multiple factors in the selection of the best antenna design, this paper presents some novel Muirhead mean operations-based aggregation operators for dealing with mF information, namely, mF Muirhead mean (mFMHM) operators, mF weighted Muirhead mean (mFWMHM) operators, mF dual Muirhead mean (mFDMHM) operators, and mF dual weighted Muirhead mean (mFDWMHM) operators. Next, some essential theoretical notions, including boundedness, monotonicity, and idempotency for the suggested operators, are studied. Further, an algorithmic multi-criteria decision-making (MCDM) approach is developed via mF Muirhead mean operations. Later, to validate the reliability and efficiency of the offered MCDM approaches, a daily-life application is considered, that is, the identification of the best antenna design in telecommunication. Finally, the effectiveness of the presented operators is verified via a detailed comparison with existing mF set-based operators.
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