Open AccessMulti-Attribute Decision Support Model Based on Bijective Hypersoft Expert Set
Author(s) -
Muhammad Nur Ihsan,
Muhammad Saeed,
Atiqe Ur Rahman,
Florentín Smarandache
Publication year - 2022
Publication title -
the punjab university journal of mathematics
Language(s) - English
Resource type - Journals
ISSN - 1016-2526
DOI - 10.52280/pujm.2022.540105
Subject(s) - disjoint sets , computer science , set (abstract data type) , bijection , data mining , soft set , argument (complex analysis) , entitlement (fair division) , decision support system , function (biology) , artificial intelligence , theoretical computer science , machine learning , mathematics , discrete mathematics , programming language , computer network , biochemistry , chemistry , evolutionary biology , biology , fuzzy logic
Soft set tackles a single set of attributes whereas its extension hypersoft set is projected for dealing attribute-valued disjoint sets corresponding to distinct attributes with entitlement of multi-argument approximate function. In order to furnish soft set-like models with multi-decisive opinions of multi-experts, a new model i.e. soft expert set has been developed but this is inadequate for handling the scenario where partitioningof attributes into their respective attribute-valued sets is necessary. Hencehypersoft expert set has made its place to be developed. This article intends to develop a new type of hypersoft set called bijective hypersoft expert set which is more flexible and effective. After characterization of its essential properties and set-theoretic operations like union, relaxed and restricted AND, a decision-support system is designed which is characterized by new operations such as decision system, reduced decision system,etc. with illustrated examples. The proposed decision-support system isapplied in multi-attribute decision-making process to manage a real-lifeapplication.