Tri-Phase Implementation of an Innovative Fuzzy Logic Approach for Decision-Making

Tarray, Tanveer Ahmad; Khaki, Zahid Gulzar; Ganie, Zahoor Ahmad; Sultan, Adil; Danish, Faizan; Albalawi, Olayan

doi:10.3390/sym16080994

Open AccessArticle

Tri-Phase Implementation of an Innovative Fuzzy Logic Approach for Decision-Making

by

Tanveer Ahmad Tarray

¹

,

Zahid Gulzar Khaki

²,

Zahoor Ahmad Ganie

³,

Adil Sultan

¹,

Faizan Danish

^4,*

and

Olayan Albalawi

⁵

¹

Department of Mathematical Sciences, Islamic University of Science and Technology, Kashmir 192122, India

²

Department of Electronics and Communication Engineering, Islamic University of Science and Technology, Kashmir 192122, India

³

Department of Electrical Engineering, Islamic University of Science and Technology, Kashmir 192122, India

⁴

Department of Mathematics, School of Advanced Sciences, VIT-AP University, Inavolu, Beside AP Secretariat, Amaravati 522237, Andhra Pradesh, India

⁵

Department of Statistics, Faculty of Science, University of Tabuk, Tabuk 47713, Saudi Arabia

^*

Author to whom correspondence should be addressed.

Symmetry 2024, 16(8), 994; https://doi.org/10.3390/sym16080994

Submission received: 30 May 2024 / Revised: 7 July 2024 / Accepted: 23 July 2024 / Published: 5 August 2024

(This article belongs to the Section B: Mathematics)

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Abstract

This paper proposes a novel approach to decision-making based on a three-phase application of a new fuzzy logic model that embraces the principles of symmetry by balancing competing objectives in data collection and analysis. Our study, which employs a three-stage stratified random sample strategy with a randomized response technique, addresses the critical challenges of cost management and volatility reduction. Using the alpha-cut method, our model creates an effective allocation strategy that finds a balance between cost constraints and variance reduction objectives. We use numerical examples from real-world scenarios to demonstrate our approach’s durability and practicality. Our revolutionary technique maintains data quality and cost-effectiveness while offering a game-changing answer to sensitive information acquisition concerns. By combining randomized response techniques and fuzzy logic, this study establishes a new standard for decision-making models that prioritizes both data-gathering precision and privacy preservation, encapsulating the essential principle of symmetry in balancing competing aims.

Keywords: stratified sampling; optimal allocation; sensitive attributes; decision-making; fuzzy logic; tri-phase implementation

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MDPI and ACS Style

Tarray, T.A.; Khaki, Z.G.; Ganie, Z.A.; Sultan, A.; Danish, F.; Albalawi, O. Tri-Phase Implementation of an Innovative Fuzzy Logic Approach for Decision-Making. Symmetry 2024, 16, 994. https://doi.org/10.3390/sym16080994

AMA Style

Tarray TA, Khaki ZG, Ganie ZA, Sultan A, Danish F, Albalawi O. Tri-Phase Implementation of an Innovative Fuzzy Logic Approach for Decision-Making. Symmetry. 2024; 16(8):994. https://doi.org/10.3390/sym16080994

Chicago/Turabian Style

Tarray, Tanveer Ahmad, Zahid Gulzar Khaki, Zahoor Ahmad Ganie, Adil Sultan, Faizan Danish, and Olayan Albalawi. 2024. "Tri-Phase Implementation of an Innovative Fuzzy Logic Approach for Decision-Making" Symmetry 16, no. 8: 994. https://doi.org/10.3390/sym16080994

APA Style

Tarray, T. A., Khaki, Z. G., Ganie, Z. A., Sultan, A., Danish, F., & Albalawi, O. (2024). Tri-Phase Implementation of an Innovative Fuzzy Logic Approach for Decision-Making. Symmetry, 16(8), 994. https://doi.org/10.3390/sym16080994

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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