Abstract
Recently, using interval-valued fuzzy soft sets to rank alternatives has become an important research area in decision-making because it provides decision-makers with the best option in a vague and uncertain environment. The present study aims to give an extensive insight into decision-making processes relying on a preference relationship of interval-valued fuzzy soft sets. Firstly, interval-valued fuzzy soft preorderings and an interval-valued fuzzy soft equivalence are established based on the interval-valued fuzzy soft topology. Then, two crisp preordering sets, namely lower crisp and upper crisp preordering sets, are proposed. Next, a score function depending on comparison matrices is expressed in solving multi-group decision-making problems. Finally, a numerical example is given to illustrate the validity and efficacy of the proposed method.
Highlights
Preordered Sets and AssociatedDecision-making is a common task associated with intelligent and complicated actions.Here, humans face situations in which they must select between many options using logic and mental processes
Feng et al [18] utilized reduced fuzzy soft sets with a level soft set of intervalvalued fuzzy soft sets to gain a better understanding of the decision-making processes as Applications in Decision-Making
The decision-making methods based on interval-valued fuzzy soft set were first used by Yang et al [17]
Summary
Decision-making is a common task associated with intelligent and complicated actions. The number of parameters fulfilled by the object may not be explained as the concept of interval-valued choice values To address this restriction, Feng et al [18] utilized reduced fuzzy soft sets with a level soft set of intervalvalued fuzzy soft sets to gain a better understanding of the decision-making processes as Applications in Decision-Making. Depending on (weighted) interval-valued fuzzy soft sets, they introduced flexible methods for decision-making procedures. The decision-making methods based on interval-valued fuzzy soft set were first used by Yang et al [17]. [22] presented a new decision-making algorithm based on two types of tables, namely the average table and the antitheses for interval-valued fuzzy soft sets, while Me et al [23] discussed two different methods.
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