Intuitionistic Fuzzy Information Research Articles

Algorithm for solving the decision-making problems based on correlation coefficients under cubic intuitionistic fuzzy information: a case study in watershed hydrological system

Cubic intuitionistic fuzzy sets (CIFSs) are a powerful and relevant medium for expressing imprecise information to solve the decision-making problems. The conspicuous feature of their mathematical concept is that it considers simultaneously the hallmarks of both the intuitionistic fuzzy sets (IFSs) and interval-valued IFSs. The present paper is divided into two parts: (i) defining the correlation measures for the CIFSs; (ii) introducing the decision-making algorithm for the CIFS information. Furthermore, few of the fundamental properties of these measures are examined in detail. Based on this, we define a novel algorithm to solve the multi-criteria decision-making process and illustrate numerical examples related to watershed’s hydrological geographical areas, global recruitment problem and so on. A contrastive analysis with several existing studies is also administered to test the effectiveness and verify the proposed method.

New prioritized aggregation operators with priority degrees among priority orders for complex intuitionistic fuzzy information

This paper aims to present some novel prioritized aggregation operators for aggregating complex intuitionistic fuzzy values (CIFVs). The aggregation operators are developed by assigning non-negative real numbers called as priority degrees among strict priority levels. The presented work is divided into three folds. The first fold is that uncertainties in the data are represented using CIFVs which have the characteristic of portraying membership and non-membership degrees over the unit disc of the complex plane. The second fold is to present prioritized averaging and geometric operators without priority degrees, prioritized averaging and geometric operators with priority degrees, prioritized ordered weighted averaging and geometric operators with priority degrees based on basic unit interval monotonic (BUM) function for aggregating dependent CIFVs. A number of propositions related to proposed operators are proved. The third fold is that a group decision-making approach based on proposed operators is developed and is applied on a decision-making problem. The results of proposed method are compared with several existing studies. The comparative study results reveal that the proposed approach is valid and gives fair results. The characteristics of the developed method are also compared with several existing approaches which highlight the superiority of the presented work over prevailing techniques. Besides this, the role of the priority degrees on aggregation result is also discussed in detail.

A new decision-making model using complex intuitionistic fuzzy Hamacher aggregation operators

Aggregation operators are the standard mathematical tool for the combination of several inputs into one unique output. This paper presents some aggregation operators for complex intuitionistic fuzzy (CIF) information. Complex intuitionistic fuzzy set (CIFS) theory has a large ability to capture vagueness since it can represent the complete specifications of problems with both intuitionistic uncertainty and periodicity. We introduce the CIF Hamacher weighted averaging (CIFHWA) operator, CIF Hamacher ordered weighted averaging (CIFHOWA) operator, CIF Hamacher weighted geometric (CIFHWG) operator and CIF Hamacher ordered weighted geometric (CIFHOWG) operator. We bring to light some remarkable properties of these operators and explicitly state some noteworthy special cases. Moreover, we contribute to the advancement of multi-attribute decision-making (MADM) with a novel proposal of an algorithm in the CIF environment. Furthermore, we consider and solve a MADM problem that finds the best source for generation of electricity with the aid of the proposed operators, thus proving their usefulness for the purpose of decision-making. Finally, we check the effectiveness of these operators by a validity test.

IF-MABAC Method for Evaluating the Intelligent Transportation System with Intuitionistic Fuzzy Information

Intelligent transportation system (ITS) is the development direction of the future traffic system. ITS can effectively employ the existing traffic facilities and ensure the safety of traffic, urban traffic, and public security management for effective control in order to satisfy people’s travel demand. Therefore, the results of the system in-depth understanding and objective evaluation are very necessary. And it is frequently regarded as a multiattribute group decision-making (MAGDM) issue. Thus, a novel MAGDM method is required to tackle it. Depending on the conventional multiattributive border approximation area comparison (MABAC) method and intuitionistic fuzzy sets (IFSs), this article designs a novel intuitive distance-based IF-MABAC method to assess the performance of financial management. First of all, a related literature review is conducted. Furthermore, some necessary theories related to IFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria are decided objectively by utilizing the maximizing deviation method. Afterwards, relying on novel distance measures between intuitionistic fuzzy numbers (IFNs), the conventional MABAC method is extended to the IFSs to calculate the final value of each enterprise. Therefore, all enterprises can be ranked, and the one with the best environmental behaviors and awareness can be identified. Eventually, an application for evaluating the intelligent transportation system and some comparative analyses have been given. The results illustrate that the designed algorithm is useful for assessing the performance of financial management.

Application of multi-attribute group decision-making methods in urban road traffic safety evaluation with interval-valued intuitionistic fuzzy information

With the development of the social economy, the level of motorization has been greatly improved, and the traffic safety problem has been paid more and more attention. In recent years, China’s road traffic accident rate showed a trend of decline after rising first, suggests that the Chinese road traffic safety level is on the decline. Road traffic safety evaluation has a positive effect in found risk factors of road traffic safety in time and reduce the traffic accident rate, so the study of traffic safety evaluation method is imperative. And the urban road traffic safety evaluation is frequently viewed as the multi-attribute group decision-making (MAGDM) problem. Depending on the conventional VIKOR method and interval-valued intuitionistic fuzzy sets (IVIFSs), this paper designs a novel IVIF-VIKOR method to assess the urban road traffic safety. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria is [Z1] decided objectively by utilizing CRITIC method. Eventually, an application and some comparative analysis are given. The results show that the designed algorithms are useful for assessing the urban road traffic safety.

Evaluation of Urban Industry-Education Integration Based on Improved Fuzzy Linguistic Approach

Integration of industry and education is a strategic measure to address the structural imbalance issues in the scientific and technological development and industrial transformation, as well as educational system. Currently, joint efforts of governments, universities, and enterprises have achieved improvements in integrating education and various related industries. However, the evaluation of industry-education integration has not received sufficient attention it deserves. Based on the context-input-process-product (CIPP) evaluation model, this paper proposes an evaluation index system for urban industry-education integration. Considering the vagueness and uncertainty of the indexes, the evaluation model is established using intuitionistic fuzzy analytic hierarchy process (IFAHP) method and 2-tuple linguistic information representation approach. A case study indicates that industry-education integration environment is the most important division of evaluation, with local regulation being the most important evaluation index. The evaluation model is proven to be effective in improving the urban industry-education integration.

Energy-cost-aware resource-constrained project scheduling for complex product system with activity splitting and recombining

Energy-cost-aware scheduling in manufacturing process has recently been considered as an effective way to use energy. In addition, applying time-of-use is regarded as one of the optimal uses of energy which the governments extend to control energy consumption. Complex product system (CoPS) has more complex and huge amounts of multiple manufacturing activities with higher energy sensibility in project scheduling than commodity products. This paper presents a new variant of resource-constrained project scheduling problem (RCPSP), which is named energy-cost-aware resource-constrained project scheduling problem with activity splitting and recombining (eRCPSP-AS&R) for CoPS. In the proposed model, a dynamic activity splitting and recombining strategy for CoPS is used by considering energy consumption. Also, a bi-objective (project delay and energy consumption cost) mathematical model is established. The solution framework of eRCPSP-AS&R model consists of two parts: activity splitting and recombining, project scheduling. The dynamic strategy of activity splitting and recombining is used to perform energy-cost-aware based on hybrid intuitionistic fuzzy information entropy, TOPSIS and fuzzy clustering method. Moreover, an improved NSGA-II algorithm is employed to solve the Pareto-optimal solutions for the proposed bi-objective optimization problem. Series of computational experiments are conducted and verified the overall performance of proposed eRCPSP-AS&R model and approaches.

Simple noncooperative games with intuitionistic fuzzy information and application in ecological management

The matrix game and bi-matrix game are typical non-cooperative games. Nowadays, interactive game decisions on social management are mainly concerned, especially when players are faced with uncertain payoffs. The aim of this paper is to develop simple and effective parameterized linear programming methods for solving two types of matrix games with payoffs expressed by intuitionistic fuzzy (IF) information. In these methods, the expected values of players are regarded as monotonic functions with their risk preferences. Hereby we construct two models of auxiliary bilinear programming, and the corresponding optimal strategies can be easily obtained by explicit computation. The models and methods proposed in this paper are applied in two ecological management problems, and the validity and applicability are verified.

Group decision making for internet public opinion emergency based upon linguistic intuitionistic fuzzy information

With the wide use of network, the outbreak of network public opinion emergencies has changed from single to multiple. The goal of the current study is to construct the emergency group decision-making (EGDM) model for multiple network public opinion emergencies under the linguistic intuitionistic environment. First of all, we introduce a new version of Copula and Co-copula named extended Copula (EAC) and extended Co-Copula (EACC), respectively, which can be used to capture the relation of attributes (indexes) in the group decision making problems of network public opinion emergencies; Some special cases of EAC and EACC are gained to manage intuitionistic fuzzy information (IFI). Besides, the novel operational rules of linguisitic intuitionistic fuzzy numbers (LIFNs) based upon EAC and EACC are also defined under linguistic intuitionistic environment. What’s more, by integrating the Choquet integral and the proposed operational rules of LIFNs, the linguistic intuitionistic fuzzy Choquet-Copula aggregation operators (LIFCCA) are proposed together with their properties are also investigated; whilst, five specific forms of LIFCCA are obtained when EAC and EACC take different generators. Last but not least, an EGDM approach is constructed based upon proposed LIFCCA; Consequently, the validities and merits of the proposed EGDM approach are shown by comparing with existing approaches.

Competition graphs with complex intuitionistic fuzzy information

A complex intuitionistic fuzzy set (CIFS) has an ability to represent the problems with intuitionistic uncertainty and periodicity, simultaneously. In this paper, we present a new framework for handling complex intuitionistic fuzzy information by combining the CIFSs with competition graphs. We first introduce the concept of complex intuitionistic fuzzy competition graphs along with its two worthwhile extensions, namely, complex intuitionistic fuzzy k-competition and complex intuitionistic fuzzy p-competition graphs. Further, we present complex intuitionistic fuzzy neighborhood graphs and m-step complex intuitionistic fuzzy competition graphs with some of their remarkable results. We also describe an application of complex intuitionistic fuzzy competition graphs along with an algorithm which finds the competition among the applicants competing for the particular jobs possessing the two-dimensional information. Moreover, we provide a comparison analysis of proposed competition graphs with existing graphs to find the validity and superiority of proposed competition graphs.

Multi-attribute group decision-making for online education live platform selection based on linguistic intuitionistic cubic fuzzy aggregation operators

The purpose of this study is to propose a multi-attribute group decision-making (MAGDM) method for online education live platform selection based on proposed novel aggregation operators (AOs) under linguistic intuitionistic cubic fuzzy set (LICFS). First, the Archimedean copula and co-copula are extended to handle linguistic intuitionistic cubic fuzzy information (LICFI) and the operational law of linguistic intuitionistic cubic fuzzy variables (LICFVs) based on extended copula (EC) and extended co-copula (ECC) are given. In addition, linguistic intuitionistic cubic fuzzy copula weighted average (LICFCWA) operator and linguistic intuitionistic cubic fuzzy copula weighted geometric (LICFCWG) operator are proposed based on EC and ECC under LICFI; meanwhile, some special forms of LICFCWA and LICFCWG have been obtained by different types generators of ECs and ECCs. Third, a novel MAGDM approach based on proposed LICFCWA (LICFCWG) is constructed to solve the selection problem of the online education live platform in the period of the COVID-19, and a detailed parameter analysis was carried out. Fourthly, LICFS will degenerate into linguistic intuitionistic fuzzy set and intuitionistic cubic fuzzy set, respectively, in different cases. Finally, some comparisons are carried out with other existing proposed MAGDM approaches. By comparing different types of experiments, the effectiveness and flexibility of the proposed approach are also showed.

Intuitionistic Fuzzy PRI-AND and PRI-OR Aggregation Operators Based on the Priority Degrees and Their Applications in Multi-Attribute Decision Making

In this paper, we investigate the multi-criteria decision making(MCDM) problems with intuitionistic fuzzy information in which the criteria are different priority levels. Based on the priority degrees, we introduce two kinds of aggregation operators: intuitionistic fuzzy PRI-AND aggregation operators based on priority degrees and intuitionistic fuzzy PRI-OR aggregation operators based on priority degrees. Then we also establish some important properties of these operators and their particular cases. Finally, we develop a new method for addressing the multi-criteria decision making(MCDM) problems in which the criteria are different priority levels based on intuitionistic fuzzy PRI-AND or PRI-OR aggregation operators based on the priority degrees. An illustrative example is provided to prove the effectiveness of the proposed approach.

Emergency Management for Large Scale Construction Projects based on Interval Valued Intuitionistic Fuzzy Information

Emergency Management for Large Scale Construction Projects based on Interval Valued Intuitionistic Fuzzy Information

Knowledge representation and reasoning with industrial application using interval-valued intuitionistic fuzzy Petri nets and extended TOPSIS

Fuzzy Petri nets (FPNs) have many successes in various applications as an important modeling technique for knowledge representation and reasoning. However, in the real world, the following conditions may make it difficult to precisely model knowledge based on current FPNs, including the cognitive nonconformity, fuzziness and uncertainty of experiential cognition of experts. In an effort to overcome the shortcomings of current FPNs, the interval-valued intuitionistic FPNs (IVIFPNs) are proposed based on interval-valued intuitionistic fuzzy sets (IVIFSs), IVIFSs hybrid averaging (IVIFSsHA) operator and extended TOPSIS (ETOPSIS). Combining with IVIFSsHA operator, an inference algorithm based on matrix operation is proposed to improve the efficiency of computing final truth values. In addition, an optimal alternative is determined based on the proposed ETOPSIS, in which intuitionistic information and fuzzy information can be considered simultaneously based on the proposed information collaborative entropy. Finally, a comparison test is presented to show the effectiveness of ETOPSIS. Moreover, a novel model for the identification of aluminum electrolysis cell condition is proposed based on IVIFPNs and ETOPSIS, and the application result shows that the proposed methods are efficient to deal with cognitive nonconformity and manage fuzziness and uncertainty of expert knowledge. These facts demonstrate the usefulness and advantages of the proposed methods in complex real-world applications.

Generalized Maclaurin symmetric mean aggregation operators based on Archimedean t-norm of the intuitionistic fuzzy soft set information

Intuitionistic fuzzy soft set (IFSS) accommodates more uncertainties within the information by considering the parameterization feature than the intuitionistic fuzzy sets and hence its applications are more extensive. Archimedean T-conorm and T-norm (ATT), consists of T-norm and T-conorm classes, is as an essential source to make the comprehensive operational laws. Meanwhile, the Maclaurin symmetric mean (MSM) has a prominent characteristic and the advantage that it can take into account the interrelation between multi-input arguments, including different attributes or different experts. Motivated by these chief characteristics, in this article, we extend the MSM operators to the IFSS based on ATT. In this paper, a method is exploited to solve the multi-criteria decision-making (MCDM) problems under the IFSS environment. To it, firstly, some generalized intuitionistic fuzzy soft operational laws are introduced based on ATT. Secondly, we reveal some averaging and geometric aggregation operators based on MSM operator. Further, some desirable features and particular cases of it are tested and build up with a new technique for illustrating MCDM problems. Finally, an illustration is given to exhibit the methodology and approach’s supremacy is shown through a comparative study with prevailing techniques.

Multi-criteria decision support systems based on linguistic intuitionistic cubic fuzzy aggregation operators

This article is an advanced approach to linguistic intuitionistic fuzzy variable through application of cubic set theory. For instance, we establish the idea of the linguistic intuitionistic cubic fuzzy variable (LICFV) theory and define several operations for LICFV; also establish a series of weighted aggregation operators under linguistic intuitionistic cubic fuzzy information, so called linguistic intuitionistic cubic fuzzy weighted averaging (LICFWA) operator, linguistic intuitionistic cubic fuzzy order weighted averaging (LICFOWA) operator, linguistic intuitionistic cubic fuzzy weighted geometric (LICFWG) operator, linguistic intuitionistic cubic fuzzy order weighted geometric (LICFOWG) operator, linguistic intuitionistic cubic fuzzy hybrid averaging (LICFHA) operator, and linguistic intuitionistic cubic fuzzy hybrid geometric (LICFHG) operator; and further study their fundamental properties and showed the relationship among these aggregation operators. In order to demonstrate the feasibility and practicality of the mentioned new technique, we develop multi-criteria decision-making algorithm under linguistic intuitionistic cubic fuzzy environment. Further, the proposed method applied to mobile phone selection, consider numerical application of mobile phone. Comparing the proposed techniques with other pre-existing aggregation operators, we concluded that the proposed technique is better, reliable, and effective.

Water Environment Management Evaluation Approach Based on IFPWA Operator under Intuitionistic Fuzzy Environment

Su, Z.X.; Zhang, G.X., and Xu, L., 2020. Water environment management evaluation approach based on IFPWA operator under intuitionistic fuzzy environment. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 229–233. Coconut Creek (Florida), ISSN 0749-0208.Water environment problem has great effect on sustainable development. Considering the fuzziness of mankind thinking as well as the complicacy of the objective world, this study establishes evaluation method under intuitionistic fuzzy environment. Firstly, by using IFPWA Operator, the evaluation information of all evaluation indexes is aggregated. Secondly, intuitionistic fuzzy entropy is applied for calculating the weights of every index. Thirdly, an evaluation method of water environment management is established by using IFPWA Operator with intuitionistic fuzzy information, where a transfer equation introduced to transform the intuitionistic fuzzy number to score is proposed. Finally, a practical example for rural water environment performance evaluation is applied to certify the feasibility and effectiveness of the method that has been proposed.

Multi-criteria IT personnel selection on intuitionistic fuzzy information measures and ARAS methodology

Global challenge and the speedy growth of information technologies compel organizations to constantly change their ways. At the present time, associations need IT personnel who create a difference by creative thoughts and who preserve with the rapid amendments. Since the evaluation of IT personnel selection (ITPS) consists of different alternatives and criteria, therefore, IT personnel selection could be regarded as a multi-criteria decision making (MCDM) problem. The doctrine of intuitionistic fuzzy sets (IFSs) is an effective tool to elucidate the uncertain information in an MCDM problem. The main objective of the paper is to choose the best IT personnel candidate by integrating intuitionistic fuzzy Additive Ratio Assessment (IF-ARAS) method with divergence measure, improved score function and IF-aggregation operators. In the developed methodology, the weights of criteria and decision experts (DEs) are computed based on proposed IF-divergence measure method intuitionistic fuzzy preference evaluation method, respectively. Next, the decision experts’ judgments are aggregated of the proposed method to evade the loss of data. Finally, the proposed IF-ARAS method is implemented to solve the IT-personnel selection (ITPS) problem to indicate the applicability of the presented approach. In addition, a comparative analysis is provided to discuss the obtained results for validating the developed methodology. The analysis illustrates that the IF-ARAS method is effective and well consistent with the existing ones.

The quantitative evaluation on the advertisement design effects with fuzzy number intuitionistic fuzzy information

The quantitative evaluation on the advertisement design effects with fuzzy number intuitionistic fuzzy information

Multi-criteria decision-making method with double risk parameters in interval-valued intuitionistic fuzzy environments

In the multi-criteria decision-making (MCDM) process, decision-makers with different risk attitudes may have different decision results. To address this issue and present decision-makers’ mentality, this paper introduces two mentality parameters. These parameters reflect the decision-makers’ risk attitudes in determining the membership and non-membership degrees of the evaluation information. In addition, the parameters demonstrate the risk attitude in terms of the hesitancy degree under interval-valued intuitionistic fuzzy information. Then, a new score function of interval-valued intuitionistic fuzzy numbers (IVIFNs) is proposed that uses the introduced mentality parameters. Meanwhile, certain properties of the proposed score function are discussed. Furthermore, the weighted comprehensive score value of IVIFNs is introduced, and an MCDM method is developed in an interval-valued intuitionistic fuzzy environment. Finally, a numerical example and comparative analyses are provided to illustrate the feasibility and effectiveness of the proposed method.