Intuitionistic Fuzzy Multi-attribute Decision Research Articles

Multi-UAV Cooperative Air Combat Target Assignment Method Based on VNS-IBPSO in Complex Dynamic Environment

This paper investigates the threat assessment method and target assignment algorithm in multi-UAV cooperative air combat decision-making. To address the uncertainty and dynamic changes in multiple threat attributes and attribute information of UAV targets, we propose a UAV target dynamic threat assessment method based on intuitionistic fuzzy multiattribute decision-making. Firstly, we propose a mixed situation information representation method to represent interval-valued fuzzy data appropriately. Secondly, we employ the normal distribution weight assignment method to fuse the multi-time situation information. Then, by incorporating the analytic hierarchy process and entropy method, we determine the normalized threat value of the target considering both objective situation data characteristics and decision-maker preferences. Finally, a simulation example is provided to validate the rationality of our proposed algorithm. For solving the multi-weapon multi-target assignment problem, a target assignment method based on the VNS-IBPSO algorithm is introduced. This method improves upon the limitations of the BPSO algorithm, such as limited local search capability and premature convergence, by combining variable neighborhood search and an improved binary particle swarm optimization algorithm. Simulation results show that the proposed threat assessment method can obtain reasonable threat assessment results under complex dynamic environments. The proposed VNS-IBPSO algorithm can solve the target assignment model quickly and efficiently based on the assessment results, therefore ensuring that the UAV mission planning system makes the correct combat plan.

An advanced approach to operational quality evaluation for industry-finance integration enterprises based on integrated interval-valued intuitionistic fuzzy multi-attribute decision making

With the acceleration of economic globalization, enterprises are facing fierce competition and huge challenges, requiring deep financial management transformation. In this context, the integration of industry and finance has gradually demonstrated extremely important value. The integration of industry and finance can not only effectively improve the efficiency of financial management, prevent business risks, and improve operational efficiency, but also enhance the comprehensive ability of enterprise financial management, providing a more flexible, transparent, and efficient financial management system for enterprises. The operational quality evaluation of industry-finance integration enterprises under lean management accounting is a multiple-attribute decision-making (MADM). In this paper, some calculating laws on IVIFSs, Hamacher sum, Hamacher product are introduced, and the interval-valued intuitionistic fuzzy Hamacher interactive power averaging (IVIFHIPA) technique is proposed based on the interval-valued intuitionistic fuzzy (IVIF) Hamacher interactive weighted averaging (IVIFHIWA) technique and power average (PA) technique. Meanwhile, some ideal properties of IVIFHIPA technique are studied. Then, the IVIFHIPA technique is employed to cope with the MADM under IVIFSs. Finally, an example for operational quality evaluation of industry-finance integration enterprises under lean management accounting is employed to test the IVIFHIPA technique. Thus, the main research aim of this paper is concluded as follows: (1) the IVIFHIPA technique is constructed based on IVIFHIWA technique and classical power average (PA) technique; (2) the IVIFHIPA technique is put forward to cope with the MADM under IVIFSs; (3) an empirical example for operational quality evaluation of industry-finance integration enterprises under lean management accounting has been put forward to show the IVIFHIPA technique.

Optimizing building material supplier selection through integrated interval-valued intuitionistic fuzzy multi-attribute decision making

In engineering construction, the unavoidable issue is how to choose suitable suppliers. The quality of suppliers has a direct impact on the progress, quality, and cost of the project. The selection of suppliers for construction projects in water conservancy and hydropower engineering is directly related to the cost of construction enterprises, and large-scale construction projects have stricter requirements for cost control. The investment in engineering construction is very huge, so cost control ability is a very important assessment indicator for construction project construction, and the cost of materials is a significant part of the construction project cost. Therefore, the research on the selection and optimization of building material suppliers is a topic that cannot be ignored. The building material supplier selection is a multi-attribute decision making (MADM). In this paper, some calculating laws on IVIFSs, Hamacher sum, Hamacher product are introduced, and the induced interval-valued intuitionistic fuzzy Hamacher interactive ordered weighted averaging (IVIFHIOWA) operators (I-IVIFHIOWA) operator is proposed. Meanwhile, some ideal properties of I-IVIFHIOWA operator are studied. Then, the I-IVIFHIOWA operator is employed to cope with the MADM under IVIFSs. Finally, an example for building material supplier selection is employed to test the I-IVIFHIOWA operator.

A novel cross-entropy framework for pattern design quality evaluation based on interval-valued intuitionistic fuzzy multi-attribute decision making

Paper packaging is favored by manufacturers in various industries due to its advantages such as economy and environmental friendliness, and the application of paper packaging in various types of products is also becoming increasingly popular. However, with the growth of the national economy and the increasing purchasing power of the people, consumers not only have higher requirements for the functionality of products, but also have higher requirements for the visual effect of product packaging. Based on the potential consumption trend of “looking for things”, enterprises need to further strengthen the artistic design effect when using paper packaging, promoting the unity of practicality and aesthetics of paper packaging. Pattern design art, as a component of graphic design art, is mainly based on pattern modeling to convey artistic concepts and aesthetic temperament. Integrating pattern design art into the process of paper packaging design can effectively enhance the artistic value of paper packaging, thereby adding color to products. The pattern design quality evaluation is a classical multi-attribute decision making (MADM). In this paper, the MADM methodology is investigated based on cross-entropy (CE) method under interval-valued intuitionistic fuzzy sets (IVIFSs) for pattern design quality evaluation. First of all, this paper extends the CE method under the IVIFSs to propose the interval-valued intuitionistic fuzzy number cross-entropy (IVIFN-CE) method, it enlarges the application range of the CE method. Secondly, a new MADM model for pattern design quality evaluation based on IVIFN-CE algorithm is proposed. In this algorithm, attribute weight is calculated by CRITIC method which is a well-known objective method. At the end of this study, we noticed to a comparison between the proposed IVIFN-CE approach with other existing methods to verify the effectiveness of the algorithm.

Water Cycle Health Assessment Using the Combined Weights and Relative Preference Relationship VIKOR Model: A Case Study in the Zheng-Bian-Luo Region, Henan Province

Both the natural and social water cycles form part of the regional water cycle, and the assessment of the health of the social water cycle provides useful recommendations for resource allocation, urban planning, and development. The Zheng-Bian-Luo region (Zhengzhou, Kaifeng, Luoyang city cluster in China) is used as an example in this study. The three-level “goal criterion index” is used to develop a water cycle index system based on deeper knowledge of the notion of the social water cycle. The system has four criterion layers that measure water quantity, utility, quality, and ecology, in addition to 22 index levels regarding the total water resources and drinking water compliance rate. By using this as a foundation, the minimum information entropy principle was applied to couple AHP (Analytic Hierarchy Process) and EFAST (Extended Fourier Amplitude Sensitivity Analysis) in order to calculate the comprehensive weights of the evaluation indicators and build a VIKOR (Intuitionistic Fuzzy Multi-attribute Decision Making Method) model of the relative preference relationship of the fused weights. This model was then compared to the conventional VIKOR model and the FCE (Fuzzy Comprehensive Evaluation Method) method in order to reflect on the objectivity of the evaluation results. The primary barriers preventing the improvement of water cycle health in the Zheng-Bian-Luo region were determined in this study by using the barrier degree model. The findings demonstrate that over the past 11 years, the overall water cycle health in the Zheng-Bian-Luo region has developed toward a healthy trend and that the water cycle health level in the region has gradually improved from the initial sub-pathological state to a healthy state. The results also demonstrate compliance with domestic drinking water sources, comprehensive water consumption per capita, the water consumption of CNY 10,000 of industrial-added value, the water consumption of CNY 10,000 of GDP, and the water consumption of CNY 10,000 for water. The primary barrier to the Zheng-Bian-Luo region’s improvement in water health is the water consumption ratio. The findings of this study can serve as a scientific foundation for creating a balanced urban water cycle and achieving long-term development in the area.

Novel intuitionistic fuzzy weighted geometric operators for intuitionistic fuzzy multi-attribute decision making

Intuitionistic fuzzy aggregation operators are crucial to the multiattribute decision making in intuitionistic fuzzy environments. In spite of this, the existing intuitionistic fuzzy weighted geometric operators in the literature have some shortcomings by which unsuitable rankings of the alternatives could be derived. In this paper, this issue is analysed and solved using the proposed diagram illustrations of these operations. Concretely, by investigating the relationships among these operators with three types of complements of the intuitionistic fuzzy numbers, some new intuitionistic fuzzy weighted geometric operators are developed and the relationships among the proposed operators and the existing ones are also verified. In particular, it is noted that all the mentioned intuitionistic fuzzy weighted geometric operators have their own drawbacks, but they are complementary each other. Finally, an approach to intuitionistic fuzzy multiattribute decision making is made based on these operators, and an example is illustrated to show the validity and the sensitivity of the proposed approach.

Interval-valued intuitionistic fuzzy multi-attribute second-order decision making based on partial connection numbers of set pair analysis

Interval-valued intuitionistic fuzzy multi-attribute second-order decision making based on partial connection numbers of set pair analysis

Research on risk assessment method of steel catenary riser based on information fusion

The Steel Catenary Riser (SCR) is an essential component connecting the subsea production system and the offshore floating platform and SCR malfunction leads to disastrous consequences. In order to ensure operation safety, the operating company monitors SCR motion response in real time by installing sensors. This paper aims to develop a multi-sensor information fusion algorithm for SCR risk assessment. The algorithm generates basic probability assignment (BPA) function based on known information. Then, the intuitionistic fuzzy multi-attribute decision matrix is constructed by BPA to evaluate the dynamic reliability of the sensor. Finally, the focal element credibility is calculated to reduce the conflict between evidences, and the improved Desert-Smarandache (DSm) theory fusion rule is utilized to evaluate the SCR risk through decision fusion. The feasibility of this method is verified by the case study. The corresponding risk control strategy is also provided.

Research on Cobot Action Decision-Making Method Based on Intuitionistic Fuzzy Set and Game Theory

The bounded rational properties of humans in human-robot collaboration (HRC) is a fundamental reason for collisions in proximity HRC. As HRC scenarios in manufacturing become increasingly popular, robot action decision-making needs to consider such properties of humans. In previous studies, humans are usually considered as rational agents whose behaviors are predictable and planned, but humans are susceptible to distractions caused by external disturbances, and different cognitive processes of the task can produce unpredictable behaviors. To better simulate human bounded rational behavior, based on an intuitionistic fuzzy (IF) multi-attribute decision algorithm, we propose a cobot action decision-making method that integrates human intention, safety, and efficiency, to produce a human-like decision. The proposed decision-making method integrates the bounded rational behavior of humans and establishes the IF set of human action intention for efficiency and comfort using cumulative prospect theory(CPT) and IF set. The proposed method lights on the human decision-making mechanism for proximity HRC actions. We use IF set to calculate the score and accuracy values of two Nash equilibria of a static chicken game, which can predict human action intentions with collision risk and provide optimal action decisions for the robot simultaneously. We generated 10,000 sets of data using the Monte Carlo method and validated the effectiveness of our proposed method by comparing it with MDP and POMDP methods. The results showed that the decision-making method could effectively perform the task of making action decisions for the robot. Simulation experiments and Turing test results show that our proposed method can predict a human’s subjective action decision intention in a situation with potential collision risk with 87.53% accuracy. At the same time, the experimental participants believe that the robot can get 4.83 out of 5 satisfaction points for an action decision.

Research on Interval-Valued Intuitionistic Fuzzy Multi-Attribute Decision Making Based on Projection Model

Background: Regarding the multi-attribute decision making where the decision information is the interval-valued intuitionistic fuzzy number and the attribute weight information is not completely determined. Methods: Intuitionistic fuzzy set theory introduces non-membership function, as an extension of the fuzzy set theory, it has certain advantages in solving complex decision-making problems. A projection model based interval-valued intuitionistic fuzzy multi-attribute decision-making scheme was proposed in this study. The objective weight of the attribute was obtained using improved intervalvalued intuitionistic fuzzy entropy, and thus the comprehensive weight of the attribute was obtained according to the preference information. Results: In the aspect of the decision-making matrix processing, the concept of interval-valued intuitionistic fuzzy ideal point and its related concepts were defined, the score vector of each scheme was calculated, the projection model was constructed to measure the similarity between each scheme and the interval-valued intuitionistic fuzzy ideal point, and the scheme was sorted according to the projection value. Conclusion: The efficiency and usability of the proposed approach are considered in the case study.

Grey relational analysis method based on cumulative prospect theory for intuitionistic fuzzy multi-attribute group decision making

The Multi-attribute group decision making (MAGDM) problem is an interesting everyday problem full of complexity and ambiguity. As an extended form of fuzzy sets, intuitionistic fuzzy sets (IFSs) can provide decision-makers (DMs) with a wider range of preferences for MAGDM. The grey relational analysis (GRA) is an effective method for dealing with MAGDM problems. However, in view of the incomplete and asymmetric information and the influence of DMs’ psychological factors on the decision result, we develop a new model that GRA method based on cumulative prospect theory (CPT) under the intuitionistic fuzzy environment. Moreover, the weight of attribute is calculated by entropy weight, so as to distinguish the importance level of attributes, which greatly improves the credibility of the selected scheme. simultaneously, the proposed method is used to the selection of optimal green suppliers for testifying the availability of this new model and the final comparison between this new method and the existing methods further verify the reliability. In addition, the proposed method provides some references for other selection problems.

A Universal Routing Algorithm Based on Intuitionistic Fuzzy Multi-Attribute Decision-Making in Opportunistic Social Networks

With the vigorous development of big data and the 5G era, in the process of communication, the number of information that needs to be forwarded is increasing. The traditional end-to-end communication mode has long been unable to meet the communication needs of modern people. Therefore, it is particularly important to improve the success rate of information forwarding under limited network resources. One method to improve the success rate of information forwarding in opportunistic social networks is to select appropriate relay nodes so as to reduce the number of hops and save network resources. However, the existing routing algorithms only consider how to select a more suitable relay node, but do not exclude untrusted nodes before choosing a suitable relay node. To select a more suitable relay node under the premise of saving network resources, a routing algorithm based on intuitionistic fuzzy decision-making model is proposed. By analyzing the real social scene, the algorithm innovatively proposes two universal measurement indexes of node attributes and quantifies the support degree and opposition degree of node social attributes to help node forward by constructing intuitionistic fuzzy decision-making matrix. The relay nodes are determined more accurately by using the multi-attribute decision-making method. Simulation results show that, in the best case, the forwarding success rate of IFMD algorithm is 0.93, and the average end-to-end delay, network load, and energy consumption are the lowest compared with Epidemic algorithm, Spray and Wait algorithm, NSFRE algorithm, and FCNS algorithm.

基于TODIM法的三角直觉模糊多属性决策算法及应用

基于TODIM法的三角直觉模糊多属性决策算法及应用

Multiattribute decision making based on converted decision matrices, probability density functions, and interval-valued intuitionistic fuzzy values

In this paper, we propose a new multiattribute decision making method based on converted decision matrices, probability density functions and interval-valued intuitionist fuzzy values. First, it obtains the converted decision matrix from the interval-valued intuitionistic fuzzy decision matrix given by the decision maker. Then, it computes the standard deviations and the mean values of the intervals appear at each row of the converted decision matrix, respectively, by using probability density functions. Then, by using the mean values and the standard deviations of the alternatives and the converted decision matrix, it gets the z-score decision matrix. Afterwards, the optimal weights of the attributes are calculated from the interval-valued intuitionist fuzzy weights of the attributes. Finally, it computes the value of overall performance of each alternative by using the z-score decision matrix and the optimal weights of the attributes for ranking the alternatives. The proposed method can conquer the shortcomings of the existing methods for interval-valued intuitionistic fuzzy multiattribute decision making.

Interval-valued intuitionistic fuzzy MADM method based on TOPSIS and grey correlation analysis.

In this paper, we propose an interval-valued intuitionistic fuzzy Multi-Attribute Decision Making (MADM) method based on improved TOPSIS and Grey Correlation Analysis (GCA), in which the attribute values are interval-valued intuitionistic fuzzy numbers. So that we can deal with imprecise information in fuzzy and rough form in MADM problems by using interval-valued intuitionistic fuzzy numbers Firstly, the concept of interval intuitionistic fuzzy entropy is introduced to calculate the entropy weight of attributes. And the combined weight is calculated by combining the entropy weight with the subjective weight. Secondly, the reverse order phenomenon in the traditional TOPSIS method is eliminated by constructing absolute Positive Ideal Solution (PIS) and absolute Negative Ideal Solution (NIS) in the form of interval-valued intuitionistic fuzzy numbers. Furthermore, the improved TOPSIS method and grey correlation analysis method are combined to describe the degree of closeness for each alternative from the ideal solution, and then the ranking and selection of each alternative are made accordingly to this degree. Finally, the rationality and effectiveness of our method are verified by an example and its sensitivity analysis. The result shows that our method makes the solution of MADM problems more objective and reasonable.

Study on location selection of client-supplied goods and materials support center for the Sichuan-Tibet railway based on dynamic intuitionistic fuzzy multi-attribute decision-making

The construction of the Sichuan-Tibet railway is encountered with some problems such as complicated geological conditions, bad climate, active plate movement, and sensitive ecological environment. Therefore, scientific and reasonable site selection is an essential guarantee for the smooth construction of the Sichuan-Tibet railway. Through constructing weighted scoring function and intuitionistic fuzzy similarity model and researching the dynamic intuitionistic fuzzy multi-attribute decision-making method considering time factor, the location decision of client-supplied goods and materials support center for Sichuan-Tibet railway construction can be complete, and the research theories and methods of location problem worldwide can be analyzed. Given the route direction and engineering construction of the Ya’an-Linzhi section of the Sichuan-Tibet railway, this paper aims to set up seven client-supplied goods and materials support centers as alternative site selection schemes, which integrates six factors (transportation, geological conditions, climate environment, site selection characteristics, engineering construction, and communication conditions) and constructs 12 index systems for client-supplied goods and materials support center location selection. Combining with the index system, the intuitionistic fuzzy decision-making matrices for four periods are established. Besides, using a dynamic intuitionistic multi-attribute decision-making method, the weighted results of similarity decision-making matrices are compared, and the location schemes of client-supplied goods and materials support centers are sequenced. The results demonstrate that Linzhi is the best site selection scheme for the construction client-supplied goods and materials support center of Ya’an to Linzhi section of the Sichuan-Tibet Railway, providing reference significance for supporting the construction of the Sichuan-Tibet Railway Project.

Improved Possibility Degree Method for Intuitionistic Fuzzy Multi-Attribute Decision Making and Application in Aircraft Cockpit Display Ergonomic Evaluation

It is very important for the intuitionistic fuzzy decision making to rank the different intuitionistic fuzzy numbers (IFNs). Based on the full information of the membership degree and non-membership degree, an improved possibility degree method is defined for dealing with multi-attribute decision making (MADM) problems in this paper. Firstly, the limitations of the existing possibility degree are discussed, and then an improved one is defined to overcome these shortcomings. Subsequently, six properties of the proposed possibility degree, which are similar to that of the classic possibility degree, are presented and proved. Moreover, some numerical examples are provided to illustrate the superiority of the proposed method. And the calculation method of membership degree and non-membership degree from the statistical viewpoint is developed to construct the intuitionistic fuzzy evaluation matrix considering that the decision-makers are difficult to give exact values of the two variables directly. Furthermore, depending on the proposed possibility degree and the intuitionistic fuzzy generalized ordered weighted geometric average (IFGOWGA) operator, a new MADM approach is employed and used to solve the practical problem of aircraft cockpit display ergonomic evaluation under the intuitionistic fuzzy set environment. Finally, an evaluation example is examined to manifest the effectiveness and feasibility of the proposed decision-making method.

A novel target threat assessment method based on three-way decisions under intuitionistic fuzzy multi-attribute decision making environment

Target threat assessment aims to rank targets threat based on their attributes and state information, which provide decision support for subsequent military decisions, e.g. weapon-target optimal assignment. Most existing threat assessment methods can only obtain ranking results, decision-makers usually need to subjectively choose priority targets to attack or interfere based on the preset threat level and ordering results, which does not meet the requirements of complex battlefield situation and uncertain information processing. A method is urgently needed, which can objectively produce threat classification results and automatically provide priority targets for combat. Therefore, we propose a novel target threat assessment method based on three-way decisions under intuitionistic fuzzy multi-attribute decision making environment. The core parts are the conditional probability of each target is estimated by intuitionistic fuzzy TOPSIS and the decision thresholds of each target are constructed by intuitionistic fuzzy evaluation values. The results of two numerical examples show that the proposed method can effectively deal with dynamic uncertain situation information, turn the traditional ranking results of two-way decisions to the objective classification results of three-way decisions and can flexibly reflect the acquisition of situation information by setting the risk avoidance coefficient.

Evidential model for intuitionistic fuzzy multi-attribute group decision making

Due to the uncertainty existing in real-world, intuitionistic fuzzy sets (IFSs) are used to model uncertain information in multi-attribute group decision making (MAGDM). The intuitionistic fuzzy MAGDM problems have gained great popularity recently. But, most of the current methods depend on various aggregation operators that may provide unreasonable collective intuitionistic fuzzy values of alternatives to be ranked. To solve such problem, a new method is developed based on evidence theory and IFSs. First, the mathematical relation between IFSs and evidence theory is analyzed, followed by the transformation from intuitionistic fuzzy evaluation information to basic belief assignment in evidence theory. Then, a new intuitionistic fuzzy weighted evidential (IFWE) average operator is introduced based on the operation of evidence discounting and evidence combination rule. We also develop a possibility-based ranking method for intuitionistic fuzzy values (IFVs) to obtain the linear ordering of IFVs. The proposed evidential model uses the IFWE average operator to aggregate the decision matrix and the attribute weight that is given by each decision maker, based on which each decision maker’s aggregated decision matrix can be obtained. Based on the decision matrices of all decision makers and the weights of the decision makers, the aggregated intuitionistic fuzzy value of each alternative can be obtained by the IFWE average operator. Finally, the preference order of all alternatives can be obtained by the possibility-based ranking method. Comparative analysis based on several application examples of MAGDM demonstrates that the proposed method can overcome the drawbacks of existing methods for MAGDM in intuitionistic fuzzy environments.

An intuitionistic fuzzy multi-attribute group decision making method with incomplete weight information based on improved VIKOR

An intuitionistic fuzzy multi-attribute group decision making method with incomplete weight information based on improved VIKOR