Entrepreneurial fuzzy group decision-making under complex environments

2018

Symmetry

This paper investigates an intuitionistic fuzzy multiple attribute decision-making method based on weighted induced distance and its application to investment selection. Specifically, an intuitionistic fuzzy weighted induced ordered weighted averaging operator is proposed to eliminate the drawbacks of existing methods by extending the functions of the order-induced variables. The main advantage of the proposed operator is its dual roles of the order-inducing variables that can simultaneously induce arguments and moderate associated weights. A further extension of the proposed operator is its adaptation towards measuring intuitionistic fuzzy information more effectively. In addition, a multiple attribute decision-making model based on the proposed distance operators is proposed. Finally, the practicability and validity of the proposed model are illustrated by using a numerical example related to investment selection.

Section: The Ifwiowawad Operatormentioning

confidence: 99%

“…Equivalently, many other special cases can be derived by analyzing the weighting vectors W, V and the order inducing variable vector U in a similar way (see [33][34][35][36]).…”

mentioning

confidence: 99%

Intuitionistic Fuzzy Multiple Attribute Decision-Making Model Based on Weighted Induced Distance Measure and Its Application to Investment Selection

Sun

2018

Symmetry

“…We can develop a number of other families of PFIOWAWA operators by employing the methodology commonly used in the OWA-related literature. [23][24][25][26]…”

Section: Families Of the Pfiowawa Operatormentioning

confidence: 99%

“…studied the application of IOWAWA in the intuitionistic fuzzy environment. Merigó et al . developed an entrepreneurial fuzzy group decision‐making procedure based on the IOWAWA operator.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A novel aggregation method for Pythagorean fuzzy multiple attribute group decision making

Baležentis

2017

Int. J. Intell. Syst.

As an extension of fuzzy set, a Pythagorean fuzzy set has recently been developed to model imprecise and ambiguous information in practical group decision‐making problems. The aim of this paper is to introduce a novel aggregation method for the Pythagorean fuzzy set and analyze possibilities for its application in solving multiple attribute decision‐making problems. More specifically, a new Pythagorean fuzzy aggregation operator called the Pythagorean fuzzy induced ordered weighted averaging‐weighted average (PFIOWAWA) operator is developed. This operator inherits main characteristics of both ordered weighted average operator and induced ordered weighted average to aggregate the Pythagorean fuzzy information. Some of main properties and particular cases of the PFIOWAWA operator are studied. A method based on the proposed operator for multiple attribute group decision making is developed. Finally, we present a numerical example of selection of research and development projects to illustrate applicability of the new approach in a multiple attribute group decision‐making problem.

A novel induced aggregation method for intuitionistic fuzzy set and its application in multiple attribute group decision making

Llopis-Albert

Zhang

2018

Int. J. Intell. Syst.

In this paper, by unifying the induced ordered weighted averaging (IOWA) and the weighted average, a novel induced aggregation method for intuitionistic fuzzy set is investigated. More specifically, a new intuitionistic fuzzy (IF) induced aggregation operator called weighted intuitionistic fuzzy IOWA weighted average (WIFIOWAWA) operator is introduced. A significant advantage of the WIFIOWAWA operator is that it can eliminate the drawback of the existing operators by the dual roles of its order‐inducing variables. In addition, some of its desired properties and families are explored. Furthermore, using the proposed operator, a procedure is developed to solve multiple attribute group decision making problems in the case of IF situation. Finally, an illustrative example is provided to demonstrate the effectiveness and practicality of the developed method.