A Similarity Measures-Based TOPSIS Method for Neutrosophic Hypersoft Set with Application in Crop Production

Authors

  • Vijay Govindarajan Distribution and Supply Technology, Expedia Group, Seattle, WA 98119, USA https://orcid.org/0009-0004-1915-1519
  • Amr Yousef Electrical Engineering Department, University of Business and Technology, Jeddah, 21432, Saudi Arabia | Engineering Mathematics Department, Alexandria University, Alexandria, 21544, Egypt https://orcid.org/0000-0003-0875-6462
  • Aleen Ijaz Chaudhary Department of Mathematics, University of Management and Technology, Lahore, Pakistan | Department of Mathematics, Faculty of Basic Sciences, Lahore Garrison University, DHA Phase 6, 54000, Lahore, Pakistan
  • Adil Ahmad Department of Computer Science and Information Technology, Virtual University of Pakistan, Pakistan
  • Zaffar Ahmed Shaikh Department of Computer Science and Information Technology, Benazir Bhutto Shaheed University Lyari, Karachi, 75660, Pakistan | School of Engineering, Ecole Polytechnique Federale de Lausanne, 1015, Lausanne, Switzerland https://orcid.org/0000-0003-0323-2061
Volume: 16 | Issue: 1 | Pages: 31863-31873 | February 2026 | https://doi.org/10.48084/etasr.15496

Received: 13 October 2025 | Revised: 6 November 2025 and 24 November 2025 | Accepted: 26 November 2025 | Online: 19 December 2025


Corresponding author: Zaffar Ahmed Shaikh

Abstract

Neutrosophic sets and hypersoft sets are both fuzzy set extensions that deal with various aspects of uncertainty and missing data. Combining these two frameworks within Multi-Criteria Decision-Making (MCDM) allows choosing an optimal solution from a wide range of scenarios and alternatives. TOPSIS is a significant practical method for evaluating and selecting numerous possibilities, which ranks preferences according to how closely they resemble the ideal solution. This study used similarity and distance measures for NHSS and aggregate NHSS decision matrices by employing aggregation operators. The proposed NHSS-TOPSIS technique was used to assess the fertility of the soil for the production of specific crops. Multiple criteria were considered to make decisions regarding crop production based on soil conditions and other factors. This work can be further broadened to various existing hybrids of hypersoft sets, such as Intuitionistic Fuzzy Hypersoft Sets (IFHSS), Pythagorean Fuzzy Hypersoft Sets (PFHSS), Bipolar fuzzy hypersoft sets, Pythagorean Fuzzy Hypersoft Matrices (PFHSM), and neutrosophic hybrids.

Keywords:

Multi-Criteria Decision-Making (MCDM), distance, similarity, Neutrosophic Hypersoft Set (NHSS), Neutrosophic Hypersoft Matrices (NHSM), TOPSIS

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V. Govindarajan, A. Yousef, A. I. Chaudhary, A. Ahmad, and Z. A. Shaikh, “A Similarity Measures-Based TOPSIS Method for Neutrosophic Hypersoft Set with Application in Crop Production”, Eng. Technol. Appl. Sci. Res., vol. 16, no. 1, pp. 31863–31873, Feb. 2026.

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