Choquet Integral Aggregation Operators Research Articles

Choquet-Integral Aggregation Operators Based on Hamacher t-Norm and t-Conorm for Complex Intuitionistic Fuzzy TOPSIS Technique to Deal With Socio-Economic Problems

Choquet-Integral Aggregation Operators Based on Hamacher t-Norm and t-Conorm for Complex Intuitionistic Fuzzy TOPSIS Technique to Deal With Socio-Economic Problems

The Approach of Induced Generalized Neutrosophic Cubic Shapley Choquet Integral Aggregation Operators via the CODAS Method to Solve Distance-Based Multicriteria Decision-Making Problems

This study aims to define a conjecture that can handle complex frames of work more efficiently that occurs in daily life problems. In decision-making theory inter-relation of criteria, weights and choice decision-making method subject to the given circumstances which are an important component for appropriate decisions. For this, we define neutrosophic cubic Shapley–Choquet integral (NCSCI) measure; combinative distance-based assessment selection (CODAS) is accomplished over NCSCI and is implemented over a numerical example of a company foreign investment model as an application in decision-making (DM) theory. The neutrosophic cubic set (NCS) is a hybrid of the neutrosophic set (NS) and interval neutrosophic set (INS), which provides a better plate form to handle inconsistent and vague data more conveniently. The novel CODAS method is based on Shapley–Choquet integral and Minkowski distance which contain more information measures than usual criteria weights and distances. The weights of criteria are measured by Shapley–Choquet integral and distance is evaluated by Minkowski distance. The Choquet integral considers the interaction among the criteria, and Shapley considers the overall weight criteria. Motivated by these characteristics NCSCI, we defined two aggregation operators’ induced-generalized neutrosophic cubic Shapley–Choquet integral arithmetic (IGNCSCIA) and operators’ induced-generalized neutrosophic cubic Shapley–Choquet integral geometric (IGNCSCIG) operators. To find the distance between two NC values, Minkowski distance is defined to evaluate neutrosophic cubic combinative distance-based assessment selection (NCCODAS). To examine the feasibility of the proposed method, an example of company investment in a foreign country is considered. To check, the validity of the method, the comparative analysis of the proposed method with other methods is conducted.

Associated Probabilities in Interactive MADM under Discrimination q-Rung Picture Linguistic Environment

In some multi-attribute decision-making (MADM) models studying attributes’ interactive phenomena is very important for the minimizing decision risks. Usually, the Choquet integral type aggregations are considered in such problems. However, the Choquet integral aggregations do not consider all attributes’ interactions; therefore, in many cases, when these interactions are revealed in less degree, they do not perceive these interactions and their utility in MADM problems is less useful. For the decision of this problem, we create the Choquet integral-based new aggregation operators’ family which considers all pair interactions between attributes. The problem under the discrimination q-rung picture linguistic and q-rung orthopair fuzzy environments is considered. Construction of a 2-order additive fuzzy measure (TOAFM) involves pair interaction indices and importance values of attributes of a MADM model. Based on the attributes’ pair interactions for the identification of associated probabilities of a 2-order additive fuzzy measure, the Shapley entropy maximum principle is used. The associated probabilities q-rung picture linguistic weighted averaging (APs-q-RPLWA) and the associated probabilities q-rung picture linguistic weighted geometric (APs-q-RPLWG) aggregation operators are constructed with respect to TOAFM. For an uncertainty pole of experts’ evaluations on attributes regarding the possible alternatives, the associated probabilities of a fuzzy measure are used. The second pole of experts’ evaluations as arguments of the aggregation operators by discrimination q-rung picture linguistic values is presented. Discrimination q-rung picture linguistic evaluations specify the attribute’s dominant, neutral and non-dominant impacts on the selection of concrete alternative from all alternatives. Constructed operators consider the all relatedness between attributes in any consonant attribute structure. Main properties on the rightness of extensions are showed: APs-q-RPLWA and APs-q-RPLWG operators match with q-rung picture linguistic Choquet integral averaging and geometric operators for the lower and upper capacities of order two. The conjugation among the constructed operators is also considered. Connections between the new operators and the compositions of dual triangular norms (Tp,Spq) and (Tmin,Smax) are also constructed. Constructed operators are used in evaluation of a selection reliability index (SRI) of candidate service centers in the facility location selection problem, when small degree interactions are observed between attributes. In example MADM, the difference in optimal solutions is observed between the Choquet integral aggregation operators and their new extensions. The difference, however, is due to the need to use indices of all interactions between attributes.

Diagnosis of lumbar degenerative disc disease by using Lp-spaces related to generalized interval-valued m-polar neutrosophic choquet integral Operator

Innovative and astonishing developments in the field of spine analysis can commence with this manuscript. The lumbar disks ([Formula: see text] to [Formula: see text]) are most commonly impaired by degeneration due to their long-standing degeneration and associated strain. We investigate the indications, purposes, risk factors, and therapies of lumbar degenerated disc disease (L-DDD). We assume that the degeneration of five discs creates many effects, making it difficult to differentiate between the different types of degenerated discs and their seriousness. Since the indeterminacy and falsity portions of science or clinical diagnosis are often ignored. Due to this complexity, the reliability of the patient’s progress report cannot be calculated, nor can the period of therapy be measured. The revolutionary concept of interval-valued m-polar neutrosophic Choquet integral aggregation operator (IVmPNCIAO) is proposed to eliminate these problems. We associate generalized interval-valued m-polar neutrosophic Choquet integral aggregation operator (GIVmPNCIAO) with the statistical formulation of [Formula: see text]-spaces and use it to identify the actual kind of degenerative disc in the lumbar spine. For the classification of interval-valued m-polar neutrosophic numbers (IVMPNNs), we set the ranking index and score function. These concepts are appropriate and necessary in order to better diagnose degeneration by associating it with mathematical modeling. We construct a pre-diagnosis map based on the fuzzy interval [Formula: see text] to classify the types of degenerative discs. We develop an algorithm by using GIVmPNCIAO based on interval-valued m-polar neutrosophic sets (IVMPNNs) to identify the degenerative disc appropriately and to choose the most exquisite treatment for the corresponding degeneration of every patient. Furthermore, we discuss the sensitivity analysis with parameter [Formula: see text] in GIVmPNCIAO to investigate the patient’s improvement record.

A Novel GSCI-Based Ensemble Approach for Credit Scoring

Credit scoring is an efficient tool for financial institutions to implement credit risk management. In recent years, many novel machine learning models have been developed for credit scoring. Among the existing machine learning models, the heterogeneous ensemble model receives much attention because of its superior performance. This paper presents a new heterogeneous ensemble model based on the generalized Shapley value and the Choquet integral. To do this, the model first uses the fuzzy measure to express the interactive characteristics between any two coalitions of base learners. Based on the accuracy and diversity objective function, a linear programming model for determining the fuzzy measure is built. To retain the original information as much as possible in the training stage, the normal fuzzy number is employed to express the base learner predicted values. Then, the generalized Shapley Choquet integral (GSCI) aggregation operator is defined to calculate the comprehensive predicted value of the ensemble model. Based on the defined aggregation operator and linear programming model, a GSCI approach is proposed for ensemble credit scoring. To illustrate the efficiency and feasibility of the GSCI approach, an experiment of thirteen machine learning models over four public credit scoring datasets and three real-world P2P leading datasets with large volumes of samples is made. Furthermore, robust tests and comparatives analysis are made to demonstrate the adaptability and performance of the GSCI-based ensemble model.

Induced Choquet Integral Aggregation Operators with Single-Valued Neutrosophic Uncertain Linguistic Numbers and Their Application in Multiple Attribute Group Decision-Making

Induced Choquet Integral Aggregation Operators with Single-Valued Neutrosophic Uncertain Linguistic Numbers and Their Application in Multiple Attribute Group Decision-Making

Biomass power generation fuel procurement and storage modes evaluation: A case study in Jilin

Biomass energy has extensive application foreground in power generation because of its economic and social benefits. Aiming at selecting the best biomass fuel procurement and storage modes in Jilin province, this paper proposes an evaluation model with linguistic hesitant fuzzy sets (LHFSs), which is good at expressing the hesitancy, inconsistency and uncertainty of subjective evaluation information. Based on cloud model and three entropy principle, the transformation between linguistic hesitant fuzzy sets and comprehensive cloud model is realized. In order to eliminate interdependency among criterion, a new Choquet integral aggregation operator based on the Sigmoid function is proposed. According to the expectation values, the ranking result of aggregated LHFSs is obtained. At last, an illustrative example of modes evaluation in Jilin province is taken in the present study to make the proposed method comprehensible. The result shows that mode 3: farmer + middleman + third-party logistics + power plant, is the most reasonable mode for Jilin biomass energy development. From the perspective of supply chain, middlemen and third party logistics can reduce the procurement and transportation cost in the supply chain, which are two bigger influential factors of fuel cost. Middlemen are not only a bridge between plants and farmers, but also the operator in the supply chain. Through the analysis of the result, suggestions from the perspective of power plants and the government are given.

Induced Choquet Integral Aggregation Operators with Single-Valued Neutrosophic Uncertain Linguistic Numbers and Their Application in Multiple Attribute Group Decision-Making

For real decision-making problems, aggregating the attributes which have interactive or correlated characteristics by traditional aggregation operators is unsuitable. Thus, applying Choquet integral operator to approximate and simulate human subjective decision-making process, in which independence among the input arguments is not necessarily assumed, would be suitable. Moreover, using single-valued neutrosophic uncertain linguistic sets (SVNULSs) can express the indeterminate, inconsistent, and incomplete information better than FSs and IFSs. In this paper, we studied the MAGDM problems with SVNULSs and proposed two single-valued neutrosophic uncertain linguistic Choquet integrate aggregation operators where the interactions phenomena among the attributes or the experts are considered. First, the definition, operational rules, and comparison method of single-valued neutrosophic uncertain linguistic numbers (SVNULNs) are introduced briefly. Second, induced single-valued neutrosophic uncertain linguistic Choquet ordered averaging (I-SVNULCA) operator and induced single-valued neutrosophic uncertain linguistic Choquet geometric (I-SVNULCG) operator are presented. Moreover, a few of its properties are discussed. Further, the procedure and algorithm of MAGDM based on the above single-valued neutrosophic uncertain linguistic Choquet integral operator are proposed. Finally, in the illustrative example, the practicality and effectiveness of the proposed method would be demonstrated.

Intuitionistic fuzzy two-sided matching model and its application to personnel-position matching problems

Personnel-position matching (PPM) problems have gained wide attention from scholars in the past decades. However, the traditional matching methodologies cannot be used to solve the two-sided matching problem between personnel and position effectively. In this article, we design an intuitionistic fuzzy two-sided matching model for the PPM problem. In order to describe the correlations between the evaluated attributes, some novel intuitionistic fuzzy Choquet integral aggregation operators are proposed. The final optimal matching results can be obtained by solving the multiobjective decision-making model. A case about the PPM problem is presented to illustrate the practicality of this method. The results of this article indicate that the intuitionistic fuzzy Choquet integral aggregation operators-based two-sided matching model can effectively solve the PPM problems where their evaluated attributes are correlated.

Pythagorean hesitant fuzzy Choquet integral aggregation operators and their application to multi-attribute decision-making

Pythagorean hesitant fuzzy sets play a vital role in decision-making as it permits a set of possible elements in membership and non-membership degrees and satisfy the condition that the square sum of its memberships degree is less than or equal to 1. While aggregation operators are used to aggregate the overall preferences of the attributes, under Pythagorean hesitant fuzzy environment and fuzzy measure in the paper we develop Pythagorean hesitant fuzzy Choquet integral averaging operator, Pythagorean hesitant fuzzy Choquet integral geometric operator, generalized Pythagorean hesitant fuzzy Choquet integral averaging operator and generalized Pythagorean hesitant fuzzy Choquet integral geometric operator. We also discuss some properties such as idempotency, monotonicity and boundedness of the developed operators. Moreover, we apply the developed operators to multi-attribute decision-making problem to show the validity and effectiveness of the developed operators. Finally, a comparison analysis is given.

A Novel Multiattribute Decision-Making Method Based on Point⁻Choquet Aggregation Operators and Its Application in Supporting the Hierarchical Medical Treatment System in China.

The hierarchical medical treatment system is an efficient way to solve the problem of insufficient and unbalanced medical resources in China. Essentially, classifying the different degrees of diseases according to the doctor’s diagnosis is a key step in pushing forward the hierarchical medical treatment system. This paper proposes a framework to solve the problem where diagnosis values are given as picture fuzzy numbers (PFNs). Point operators can reduce the uncertainty of doctor’s diagnosis and get intensive information in the process of decision making, and the Choquet integral operator can consider correlations among symptoms. In order to take full advantage of these two kinds of operators, in this paper, we firstly define some point operators under the picture fuzzy environment, and further propose a new class of picture fuzzy point–Choquet integral aggregation operators. Moreover, some desirable properties of these operators are also investigated in detail. Then, a novel approach based on these operators for multiattribute decision-making problems in the picture fuzzy context is introduced. Finally, we give an example to illustrate the applicability of the new approach in assisting hierarchical medical treatment system. This is of great significance for integrating the medical resources of the whole society and improving the service efficiency of the medical service system.

Shapley interval-valued dual hesitant fuzzy Choquet integral aggregation operators in multiple attribute decision making

Shapley interval-valued dual hesitant fuzzy Choquet integral aggregation operators in multiple attribute decision making

Some new interval-valued dual hesitant fuzzy Choquet integral aggregation operators and their applications

Some new interval-valued dual hesitant fuzzy Choquet integral aggregation operators and their applications

CHOQUET INTEGRALS OF WEIGHTED TRIANGULAR FUZZY LINGUISTIC INFORMATION AND THEIR APPLICATIONS TO MULTIPLE ATTRIBUTE DECISION MAKING

We investigate the multiple attribute decision making problems in which attribute values take the form of triangular fuzzy linguistic information. Firstly, the definition and some operational laws of triangular fuzzy linguistic are introduced. Then, we have developed three fuzzy linguistic Choquet integral aggregation operators: fuzzy linguistic choquet ordered averaging operator, fuzzy linguistic choquet ordered geometric operator and fuzzy linguistic choquet ordered harmonic mean operator. The prominent characteristic of the operators is that they cannot only consider the importance of the elements or their ordered positions, but also reflect the correlation among the elements or their ordered positions. We have studied some desirable properties of these operators, such as commutativity, idempotency and monotonicity, and applied these operators to multiple attribute decision making with triangular fuzzy linguistic information. Finally an illustrative example has been given to show the developed method.

AN APPROACH TO MULTIPLE ATTRIBUTE DECISION MAKING BASED ON THE INDUCED CHOQUET INTEGRAL WITH FUZZY NUMBER INTUITIONISTIC FUZZY INFORMATION

In this paper, we investigate the multiple attribute decision making problems with fuzzy number intuitionistic fuzzy information. Firstly, some operational laws of fuzzy number intuitionistic fuzzy values, score function and accuracy function of fuzzy number intuitionistic fuzzy values are introduced. Then, we have developed two fuzzy number intuitionistic fuzzy Choquet integral aggregation operators: induced fuzzy number intuitionistic fuzzy choquet ordered averaging (IFNIFCOA) operator and induced fuzzy number intuitionistic fuzzy choquet ordered geometric (IFNIFCOG) operator. The prominent characteristic of the operators is that they can not only consider the importance of the elements or their ordered positions, but also reflect the correlation among the elements or their ordered positions. We have studied some desirable properties of the IFNIFCOA and IFNIFCOG operators, such as commutativity, idempotency and monotonicity, and applied the IFNIFCOA and IFNIFCOGM operators to multiple attribute decision making with fuzzy number intuitionistic fuzzy information. Finally an illustrative example has been given to show the developed method.

Multi-criteria group decision making method based on interval 2-tuple linguistic information and Choquet integral aggregation operators

Considering that interval 2-tuple linguistic model can solve the interval linguistic multi-criteria decision-making problems, and Choquet integral can deal with the multi-criteria group decision-making problems with correlated criteria, in the revelation of these two methods, this paper combined them together to cope with the interval linguistic multi-criteria group decision-making problems with correlated criteria. Because of the limitations of 2-tuple linguistic representation model, a modified composite scale based on 2-tuple linguistic model was proposed which can better improve the accuracy of decision-making. First, using Choquet integral and interval 2-tuple linguistic model, two aggregation operators with their properties were introduced to better reflect correlations among criteria, i.e., the interval 2-tuple correlated averaging operator and the interval 2-tuple correlated geometric operator. Then, a multi-criteria group decision-making method based on the above operators was proposed. Finally, the proposed method was compared with the existing ones based on the same illustrative example to confirm its feasibility and rationality.

Uncertain generalized aggregation operators

The aim of this paper is to extend the generalized ordered weighted averaging operator and provide a new class of operators called the uncertain generalized ordered weighted averaging (UGOWA) operator. It provides a very general formulation that includes as special cases a wide range of aggregation operators and aggregates the input arguments taking the form of intervals rather than exact numbers. We further generalize the UGOWA operator to obtain the uncertain generalized hybrid averaging operator, the quasi uncertain ordered weighted averaging operator and the uncertain generalized Choquet integral aggregation operator. In the meanwhile, a new approach to determining the UGOWA weights is proposed based on the relative deviation measure. Finally, a numerical example is presented to illustrate the proposed approach to group decision making with UGOWA operator.

Fuzzy induced generalized aggregation operators and its application in multi-person decision making

We present a wide range of fuzzy induced generalized aggregation operators such as the fuzzy induced generalized ordered weighted averaging (FIGOWA) and the fuzzy induced quasi-arithmetic OWA (Quasi-FIOWA) operator. They are aggregation operators that use the main characteristics of the fuzzy OWA (FOWA) operator, the induced OWA (IOWA) operator and the generalized (or quasi-arithmetic) OWA operator. Therefore, they use uncertain information represented in the form of fuzzy numbers, generalized (or quasi-arithmetic) means and order inducing variables. The main advantage of these operators is that they include a wide range of mean operators such as the FOWA, the IOWA, the induced Quasi-OWA, the fuzzy IOWA, the fuzzy generalized mean and the fuzzy weighted quasi-arithmetic average (Quasi-FWA). We further generalize this approach by using Choquet integrals, obtaining the fuzzy induced quasi-arithmetic Choquet integral aggregation (Quasi-FICIA) operator. We also develop an application of the new approach in a strategic multi-person decision making problem.

Continuous generalized OWA operator and its application to decision making

In this paper we present a new class of operators called the continuous generalized ordered weighted averaging (C-GOWA) operators, which extends the continuous ordered weighted averaging operator. To adapt to uncertain and complex situations in decision making, we use differentiated aggregation method and produce special forms of C-GOWA operator. In addition, we apply the C-GOWA operator to the aggregation of multiple interval arguments and obtain a wide range of aggregation operators. We especially discuss the controlling parameter and the selection of basic unit-interval monotonic function, introduced in the information aggregation, to make it more feasible. We further generalize the previous approaches by using Choquet integral and quasi-arithmetic means, obtaining the combined continuous generalized Choquet integral aggregation operator and the combined continuous quasi-arithmetic Choquet integral aggregation operator. We also present some further extension by using hierarchical aggregation rules, obtaining the ordered hierarchies of the combined C-GOWA operator. Meanwhile, some desirable properties of these operators are investigated. Finally, we give a numerical example to illustrate the application of these operators to group decision making with interval arguments.

OWA aggregation of intuitionistic fuzzy sets

We recall the concept of an intuitionistic fuzzy subset (IFS). Fundamental to an IFS is the fact that it is defined using two values, a degree of membership and degree of non-membership. The ordered weighted averaging (OWA) operator is introduced and several of its features are described. Particularly notable is the idea of the dual of an OWA operator. We next discuss the aggregation of a collection of IFS using a prescribed OWA operator. It is shown that while the aggregation of the degrees of membership is performed using the prescribed OWA operator, the aggregation of the degrees of non-membership requires use of the dual of the prescribed OWA operator. The Choquet integral aggregation operator is introduced and applied to the aggregation of IFSs. Here again the concept of the dual is needed to perform the aggregation of the degrees of non-membership. We also discuss the aggregation of IFSs using the Sugeno integral. Fundamental to this work is our realisation of the importance of the concept of the dual operators in dealing with the aggregation of IFS.