SuperHyperSoft Sets Using Python and its Applications in  Neutrosophic SuperHyperSoft Sets under TOPSIS Method

T. Kiruthika; M. Karpagadevi; S. Krishnaprakash; G. Deepa

Authors

T. Kiruthika Department of Mathematics, Sri G.V.G Visalakshi College for Women, Tamilnadu, India;
M. Karpagadevi Department of Mathematics, Sri G.V.G Visalakshi College for Women, Tamilnadu, India;
S. Krishnaprakash Department of Mathematics, Sri Krishna College of Engineering and Technology, Coimbatore, India.
G. Deepa Department of Computer Science, Dr. Mahalingam College of Engineering and Technology, India.

Keywords:

Soft Set; Neutrosophic Set; Neutrosophic SuperHyperSoft Set; TOPSIS method; MCDM.

Abstract

In this paper, we present an integrated framework that combines python-based
implementation of SuperHyperSoft Sets (SHSSs) with a robust Multi-Criteria Decision Making
(MCDM) model using Neutrosophic SuperHyperSoft Sets (NSHSSs) and the Technique for Order
Preference by Similarity to Ideal Solution (TOPSIS) method. This framework is designed to address
complex decision-making problems under uncertainty, vagueness and indeterminacy, particularly in
academic contexts such as selecting an optimal Q1 journal for manuscript submission. The
implementation constructs power sets of hierarchical sub-criteria, computes Cartesian products and
generates NSHSS-based logical propositions to enable a structured and dynamic analysis. The model
incorporates linguistic evaluations from multiple decision makers, converting them into Neutrosophic
Sets (NSs) and computing decision-maker weights based on true (T), indeterminacy (I) and false (F)
values. A case study involving the evaluation of four top-tier journals across six major criteria
demonstrates the applicability and effectiveness of the proposed method. The resulting decision
matrix, ideal solutions, and closeness coefficients illustrate how this approach enhances realism,
sensitivity and objectivity in MCDM scenarios.

DOI: 10.5281/zenodo.16884384