17,291 research outputs found
Pythagorean 2-tuple linguistic power aggregation operators in multiple attribute decision making
In this paper, we investigate the multiple attribute decision making
problems with Pythagorean 2-tuple linguistic information.
Then, we utilize power average and power geometric operations
to develop some Pythagorean 2-tuple linguistic power aggregation
operators: Pythagorean 2-tuple linguistic power weighted
average (P2TLPWA) operator, Pythagorean 2-tuple linguistic power
weighted geometric (P2TLPWG) operator, Pythagorean 2-tuple linguistic
power ordered weighted average (P2TLPOWA) operator,
Pythagorean 2-tuple linguistic power ordered weighted geometric
(P2TLPOWG) operator, Pythagorean 2-tuple linguistic power
hybrid average (P2TLPHA) operator and Pythagorean 2-tuple linguistic
power hybrid geometric (P2TLPHG) operator. The prominent
characteristic of these proposed operators are studied. Then,
we have utilized these operators to develop some approaches to
solve the Pythagorean 2-tuple linguistic multiple attribute decision
making problems. Finally, a practical example for enterprise
resource planning (ERP) system selection is given to verify the
developed approach and to demonstrate its practicality and
effectiveness
Generalized Hamacher aggregation operators for intuitionistic uncertain linguistic sets: Multiple attribute group decision making methods
© 2019 by the authors. In this paper, we consider multiple attribute group decision making (MAGDM) problems in which the attribute values take the form of intuitionistic uncertain linguistic variables. Based on Hamacher operations, we developed several Hamacher aggregation operators, which generalize the arithmetic aggregation operators and geometric aggregation operators, and extend the algebraic aggregation operators and Einstein aggregation operators. A number of special cases for the two operators with respect to the parameters are discussed in detail. Also, we developed an intuitionistic uncertain linguistic generalized Hamacher hybrid weighted average operator to reflect the importance degrees of both the given intuitionistic uncertain linguistic variables and their ordered positions. Based on the generalized Hamacher aggregation operator, we propose a method for MAGDM for intuitionistic uncertain linguistic sets. Finally, a numerical example and comparative analysis with related decision making methods are provided to illustrate the practicality and feasibility of the proposed method
Induced hesitant 2-tuple linguistic aggregation operators with application in group decision making
In this article, hesitant 2-tuple linguistic arguments are used to evaluate the group decision making problems which have inter dependent or inter active attributes. Operational laws are developed for hesitant 2-tuple linguistic elements and based on these operational laws hesitant 2- tuple weighted averaging operator and generalized hesitant 2- tuple averaging operator are proposed. Combining Choquet integral with hesitant 2-tuple linguistic information, some new aggregation operators are defined, including the hesitant 2-tuple correlated averaging operator, the hesitant 2-tuple correlated geometric operator and the generalized hesitant 2-tuple correlated averaging operator. These proposed operators successfully manage the correlations among the elements. After investigating the properties of these operators, a multiple attribute decision making method based on these operators, is suggested. Finally, an example is given to illustrate the practicality and feasibility of proposed method
Some hesitant fuzzy geometric operators and their application to multiple attribute group decision making
Hesitant fuzzy set (HFS), a generalization of fuzzy set (FS), permits the membership degree of an element of a set to be represented as several possible values between 0 and 1. In this paper, motivated by the extension principle of HFs, we export Einstein operations on FSs to HFs, and develop some new aggregation operators, such as the hesitant fuzzy Einstein weighted geometric operator, hesitant fuzzy Einstein ordered weighted geometric operator, and hesitant fuzzy Einstein hybrid weighted geometric operator, for aggregating hesitant fuzzy elements. In addition, we discuss the correlations between the proposed aggregation operators and the existing ones respectively. Finally, we apply the hesitant fuzzy Einstein weighted geometric operator to multiple attribute group decision making with hesitant fuzzy information. Some numerical examples are given to illustrate the proposed aggregation operators.
First published online: 09 Jun 201
Power of Continuous Triangular Norms with Application to Intuitionistic Fuzzy Information Aggregation
The paper aims to investigate the power operation of continuous triangular
norms (t-norms) and develop some intuitionistic fuzzy information aggregation
methods. It is proved that a continuous t-norm is power stable if and only if
every point is a power stable point, and if and only if it is the minimum
t-norm, or it is strict, or it is an ordinal sum of strict t-norms. Moreover,
the representation theorem of continuous t-norms is used to obtain the
computational formula for the power of continuous t-norms. Based on the power
operation of t-norms, four fundamental operations induced by a continuous
t-norm for the intuitionistic fuzzy (IF) sets are introduced. Furthermore,
various aggregation operators, namely the IF weighted average (IFWA), IF
weighted geometric (IFWG), and IF mean weighted average and geometric (IFMWAG)
operators, are defined, and their properties are analyzed. Finally, a new
decision-making algorithm is designed based on the IFMWAG operator, which can
remove the hindrance of indiscernibility on the boundaries of some classical
aggregation operators. The practical applicability, comparative analysis, and
advantages of the study with other decision-making methods are furnished to
ascertain the efficacy of the designed method
Elevating decision management in sustainable energy planning through spherical fuzzy aggregation operators
This article introduces a novel paradigm for enhancing the administration of decisions regarding sustainable energy planning. This is achieved by deploying novel spherical fuzzy aggregation operators that have been meticulously tailored to address the inherent complexities of uncertainty and imprecision prevalent in energy planning datasets. These operators vastly increase the precision and efficacy of decision-making processes, thereby transforming the entire sustainable energy landscape. This study focuses predominantly on the complex domain of multi-attribute decision-making (MADM), in which the interplay of parameters is characterized by a discernible hierarchy of importance. This method generates aggregation operators based on the assignment of non-negative real values to clearly defined priority echelons, a framework known as priority degrees. This effort results in the development of two notable prioritized operators: the “spherical fuzzy prioritized averaging operator with priority degrees” and the “spherical fuzzy prioritized geometric operator with priority degrees”. The efficacy of these conceptual frameworks is vividly demonstrated through the application of extensive case studies, in which observable results clearly demonstrate their superiority over conventional methodologies. The empirical findings unequivocally demonstrate the superiority of the proposed operators, resonating with substantial performance and efficiency improvements. This study not only adds a seminal dimension to the field of sustainable energy management but also reveals a revolutionary application of spherical fuzzy aggregation operators at the forefront of effective decision-making paradigms. The seamless fusion of theoretical innovation and practical utility outlines a path forward, with transformative prospects and far-reaching implications for the sustainable energy landscape
The Unbalanced Linguistic Aggregation Operator in Group Decision Making
Published version of an article in the journal: Mathematical problems in engineering. Also available from Hindawi: http://dx.doi.org/10.1155/2012/619162Many linguistic aggregation methods have been proposed and applied in the linguistic decision-
making problems. In practice, experts need to assess a number of values in a side of reference
domain higher than in the other one; that is, experts use unbalanced linguistic values to express
their evaluation for problems. In this paper, we propose a new linguistic aggregation operator to
deal with unbalanced linguistic values in group decision making, we adopt 2-tuple representation
model of linguistic values and linguistic hierarchies to express unbalanced linguistic values, and
moreover,we present the unbalanced linguistic ordered weighted geometric operator to aggregate
unbalanced linguistic evaluation values; a comparison example is given to show the advantage of
ourmethod
Aggregation Weights for Linguistic Hybrid Geometric Averaging Operator
This paper tries to point out that the aggregation weights in linguistic hybrid geometric averaging
operator will dominate the final result of the ranking for alternatives. We examined the linguistic hybrid geometric
averaging operator that was proposed by previous studies and found it contained several questionable results. The
major defect of the previous approach was that it failed to demonstrate two core factors: accuracy and speed, both of
which have been explicitly uncovered and discussed in the study. With previous work the pivotal and dominant element,
distribution of weights, in finding subjectively by decision maker of linguistic hybrid geometric averaging operators
for group decision-making problems, lacks solid foundation and is unjustified. Here we provide the mathematical
rationale and reliable advices, to point out that deficiency. In addition, we have detected and rectified some
redundancies of operational laws in the procedure of previous study due to the improper utilization of negative
operators. It certainly should be noted that the careless applications of those highly dependant operators may
significantly diminish the efficiency and performance of entire mechanism for decision making under fuzzy
environment. We develop an easy aggregation approach based on the arithmetic mean to solve the most favorable
alternative problem. A comprehensive numerical examination of 1296 tests supports our result
NORMALIZED WEIGHTED GEOMETRIC BONFERRONI MEAN OPERATOR OF INTERVAL ROUGH NUMBERS – APPLICATION IN INTERVAL ROUGH DEMATEL-COPRAS MODEL
This paper presents a new approach to the treatment of uncertainty and imprecision in multi-criteria decision-making based on interval rough numbers (IRN). The IRN-based approach provides decision-making using only internal knowledge for the data and operational information of a decision-maker. A new normalized weighted geometric Bonferroni mean operator is developed on the basis of the IRN for the aggregation of the IRN (IRNWGBM). Testing of the IRNWGBM operator is performed through the application in a hybrid IR-DEMATEL-COPRAS multi-criteria model which is tested on real case of selection of optimal direction for the creation of a temporary military route. The first part of hybrid model is the IRN DEMATEL model, which provides objective expert evaluation of criteria under the conditions of uncertainty and imprecision. In the second part of the model, the evaluation is carried out using the new interval rough COPRAS technique
A Novel Multiple Attribute Satisfaction Evaluation Approach with Hesitant Intuitionistic Linguistic Fuzzy Information
This paper investigates the multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant intuitionistic linguistic fuzzy element (HILFE). Firstly, motivated by the idea of intuitionistic linguistic variables (ILVs) and hesitant fuzzy elements (HFEs), the concept, operational laws, and comparison laws of HILFE are defined. Then, some aggregation operators are developed for aggregating the hesitant intuitionistic linguistic fuzzy information, such as hesitant intuitionistic linguistic fuzzy weighted aggregation operators, hesitant intuitionistic linguistic fuzzy ordered weighted aggregation operators, and generalized hesitant intuitionistic linguistic fuzzy weighted aggregation operators. Moreover, some desirable properties of these operators and the relationships between them are discussed. Based on the hesitant intuitionistic linguistic fuzzy weighted average (HILFWA) operator and the hesitant intuitionistic linguistic fuzzy weighted geometric (HILFWG) operator, an approach for evaluating satisfaction degree is proposed under hesitant intuitionistic linguistic fuzzy environment. Finally, a practical example of satisfaction evaluation for milk products is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness
- …