Stochastic multiple attribute decision making with Pythagorean hesitant fuzzy set based on regret theory.

The objective of this paper is to present an extended approach to address the stochastic multi-attribute decision-making problem. The novelty of this study is to consider the regret behavior of decision makers under a Pythagorean hesitant fuzzy environment. First, the group satisfaction degree of decision-making matrices is used to consider the different preferences of decision-makers. Second, the nonlinear programming model under different statues is provided to compute the weights of attributes. Then, based on the regret theory, a regret value matrix and a rejoice value matrix are constructed. Furthermore, the feasibility and superiority of the developed approach is proven by an illustrative example of selecting an air fighter. Eventually, a comparative analysis with other methods shows the advantages of the proposed methods.

Optimal pathways for upgrading China's wastewater treatment plants for achieving water quality standards at least economic and environmental cost.

Wastewater treatment plants (WWTPs) in China must be upgraded to meet new discharge standards, but this incurs both economic and environmental costs and benefits. To select the optimal upgrade pathway, we developed ten upgrade paths based on two common decision-making scenarios for WWTP upgrade in developing countries. Using model simulation, life-cycle assessment, life-cycle cost, and multiple-attribute decision-making, we incorporated the full costs and benefits associated with the construction and operation into the decision-making process. We used a weighting scheme of attributes for the three regions and ranked the upgrade paths using the technique for order preference by similarity to an ideal solution (TOPSIS). The results showed that constructed wetlands and sand filtration were advantageous in terms of lower economic costs and environmental impacts, while the denitrification filter pathways required less land. Optimal pathways differed by region, highlighting the importance of a detailed and integrated assessment of the costs and benefits of WWTP upgrade options over the full life cycle. Our findings can inform decision-making on upgrading China's WWTPs to meet stringent discharge standards and protect inland water and coastal environments.

Research on layout model and construction planning of aged care institutions for disabled elders in China: based on Nanjing city data.

BACKGROUND: To meet the needs of diversified pension services and the construction of aged care institutions is one of the urgent livelihood issues in China. Under the major national needs of pension and care for the elderly, it is necessary to optimize the allocation of pension and care for the elderly resources, and formulate operational coping strategies and optimization plans. It is of great significance to deal with the urgent problem of population aging in a timely and scientific way. METHODS: The economic benefits and social costs of aged care institutions are regarded as objective functions. To satisfy the economic benefits, it is necessary to reduce the social costs, and its construction quantity can only be an integer. The multi-objective genetic algorithm is improved with integer programming, and the global optimal solution is achieved after several times of searching. Under the multi-objective optimization model, the improved genetic algorithm was combined with the superior and inferior solution distance method to solve the genetic algorithm, and the corresponding objective function value was obtained after rounding. Finally, Pareto optimal solution set is selected by multi-objective decision, and the result of construction planning is obtained. RESULTS: Based on multi-attribute decision analysis and taking three years as the construction cycle, the planning scheme of aged care institutions construction in each district of Nanjing in the next 15 years was proposed. In addition, considering the intelligent trend of future pension, the proportion of home-based pension is increasing year by year, and the model is promoted to meet the needs of diversified pension services. With the gradual increase of the elderly population in Nanjing, the proportion of intelligent home-based care has been increasing year by year since 2027, and the construction demand of aged care institutions has also increased. The number of construction at all levels rises gradually in each cycle, and the increase is more obvious after 2027. CONCLUSIONS: The layout and planning of aged care institutions proposed in this paper not only considers economic and environmental benefits, but also combines the current situation of aged care institutions in various districts of Nanjing. The model is reasonable and effective, and has practical application value. It will help China optimize the allocation of elderly care resources under the target of active aging, and scientifically and comprehensively deal with the problem of population aging.

[Analysis of Critical Source of Potentially Harmful Elements in Urban Road Dust During Winter in Taiyuan Based on Multiple Attribute Decision Making Method].

In order to analyze the critical sources of potential harmful elements (PHEs) in road dust from Taiyuan during winter, 40 road dust samples were collected. The contents of PHEs, including As, Cd, Pb, Ni, Cr, Cu, and Zn, in the road dust samples were measured using inductively coupled plasma mass spectrometry and atomic fluorescence spectrometry. The ecological risks and human health risks posed by dust PHEs were assessed using NIRI and a health risk evaluation model recommended by USEPA, respectively. The sources of dust PHEs were identified by using the combination of principal component analysis and positive matrix factorization (PMF); the total PHE contents and the ecological risks and human health risks posed by PHEs in dust were apportioned to the PHE sources based on the PMF results; subsequently, the critical source of dust PHEs was determined using the multiple attribute decision making method (MADM). The results demonstrated that: 1 the average concentrations of As, Cd, Pb, Ni, Cr, Cu, and Zn were 17.92, 0.32, 69.10, 30.06, 107.74, 73.37, and 268.49 mg·kg-1, respectively, which were higher than the corresponding background values of soil in Taiyuan, indicating that the PHEs had accumulated in road dust; the mean value of NIRI was 63.86, demonstrating that PHEs in dust posed moderate risks, and the dust PHEs pollution was controllable. 2 Human health risk assessment indicated that exposure to PHEs in dust did not pose serious non-carcinogenic or carcinogenic risks. Ingestion was the most important pathway for exposure to PHEs in road dust that damages human health, and As and Cr have been found to pose the most risks among the seven PHEs. 3 The present study found three main sources of PHEs measured in the dust: natural, traffic, and industrial, which accounted for 35.95%, 40.25%, and 23.82% of the total concentrations of PHEs, respectively. 4 Industrial emissions contributed the least to the total PHEs contents in dust; however, the PHEs released from industrial sources caused relatively high risks, with the results of MADM indicating that industrial sources were the most critical source for dust PHEs. Our results indicated that the critical source identification of PHEs, which was determined to be the most pernicious source, could provide reference for subsequent pollution source control.

Using hybrid consistent fuzzy preference relations-importance-performance analysis model to improve shared decision-making quality based on orthopaedic nurses' perceptions.

PURPOSE: To understand key factors for shared decision-making (SDM) and the quality improvement of nursing decisions in the orthopaedic clinical environment. METHOD: This study applied the consistent consistent fuzzy preference relations (CFPRs) and importance-performance analysis (IPA) methods to explore the attribute weights and SDM performance, respectively. The dataset was collected from 16 orthopaedic clinical nurses' experiences in a third-grade and first-level general hospital in Taizhou, China. This study was performed according to the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines. RESULTS: The results showed that "I made clear to my patient or patient's family that a nursing care decision needs to be made", "I explained the advantages and disadvantages of the nursing care options to my patient or patient's family" and "I told my patient or patient's family that there are different nursing care options for caring his/her medical condition" were key factors for affecting SDM. The statistical significance confidence and difference error of weight results were 98.321% and 1.679%, respectively. In addition, "I asked my patient or patient's family which nursing care option he/she prefers" was the key factor for improving orthopaedic clinical nursing in the case hospital. CONCLUSION: The hybrid CFPRs-IPA model can help hospital managers effectively understand the key factors of SDM quality and improve the orthopaedic clinical nursing performance from nurses' perspectives. RELEVANCE TO CLINICAL PRACTICE: A quantitative decision-making model can help nurses understand the key factors affecting the quality of SDM in nursing decision-making and promote nursing decision-making and patient-centred nursing service quality. A series of corresponding SDM training courses (i.e. concepts, knowledge and skills) can be provided for hospital and nursing department managers to maximise the potentially available resources. PATIENT OR PUBLIC CONTRIBUTION: The clinical care process should be committed to involving patients in their care decisions and also provide an opportunity for patients to gain a comprehensive understanding of the care decision-making process in order to inform future patient contributions to care decisions.

Fermatean fuzzy soft aggregation operators and their application in symptomatic treatment of COVID-19 (case study of patients identification).

ABSTRACT: The main focus of this paper is the application of aggregation operators (AOs) in the environment of Fermatean fuzzy soft sets (FFSS). The unique feature of the work is its application in the symptomatic treatment of the COVID-19 disease. For this purpose, the idea of FFSS is introduced which is based on the Senapati and Yagar's Fermatean fuzzy set. Next we have defined Fermatean fuzzy soft aggregation operators (FFSAOs) like, Fermatean fuzzy soft weighted averaging (FFSWA) operator, Fermatean fuzzy soft ordered weighted averaging (FFSOWA) operator, Fermatean fuzzy soft weighted geometric (FFSWG) operator and Fermatean fuzzy soft ordered weighted geometric (FFSOWG). The prominent properties of these operators are given in details. We have also developed some approaches to solve multi-criteria decision making (MCDM) problems in Fermatean fuzzy soft (FFS) information. An introduction to the novel pandemic, safety measures, and then its possible symptomatic treatment is also provided. The developed operators are utilized in the symptomatic treatment of COVID-19 disease in order to show the practical applications and importance of these AOs as well as Fermatean fuzzy soft information. The stability of the proposed work is also proved by the comparative analysis.

Application of Rough Set Theory to Improve Outpatient Medical Service Quality in Public Hospitals Based on the Patient Perspective.

Purpose: To analyze the key factors and decision-making behaviors affecting overall satisfaction based on perceptual data of outpatients. Methods: The official satisfaction questionnaire developed by the National Health Commission of the People's Republic of China was used. Rough set theory was used to identify the perception patterns between condition attributes (i.e., service factors) and a decision attribute (i.e., overall service level) and to express them in rule form (i.e., if-then). Results: The four minimal-coverage rules, with strength exceeding 10% in the good class, and six crucial condition attributes were obtained: "Ease of registration (C1)," "Respected by registered staff (C2)," "Registered staff's listening (C3)," "Respected by doctor (C9)," "Signpost (C12)," and "Privacy (C16)." In addition, the average hit rate for 5-fold cross-validation was 90.86%. Conclusions: A series of decision rules could help decision-makers easily understand outpatients' situations and propose more suitable programs for improving hospital service quality because these decision rules are based on actual outpatient experiences.

A novel picture fuzzy linguistic Muirhead Mean aggregation operators and their application to multiple attribute decision making.

The Picture fuzzy linguistic set (PFLS) is an extension of the intuitionistic fuzzy set (IFS) and linguistic variables (LVs), which has been applied successfully in the process of decision making. Considering the lack of closeness of extant PFLS operations and the interrelationship among input attributes do not consider. In this paper, for the sake of addressing those limitations, we firstly redefine some novel operational laws for PFLS by introducing linguistic scale functions and the related properties are studied. Then, a novel score function and accuracy function are also defined to compare PFLSs. Subsequently, in consideration of the superiority of the Muirhead Mean (MM) operator in capturing the interaction relationship between the input parameters, we extend the MM operator to the Picture fuzzy linguistic context and then propose Picture fuzzy linguistic weighted MM operator and its dual form in a new light. After that, these operators have adopted to build two novel models to solve multiple attribute decision-making (MADM) problems. Finally, a practical example for the selection of the innovative "Mobike" sharing bike design is provided to illustrate the practicality and effectiveness of proposed approaches.

Topic selection for health technology assessment: An approach combining multiple attribute decision making and decision rules.

Background: Various studies have used multiple attribute decision making (MADM) techniques to assess and rank health technologies. The goal of the present study was to prioritize health technologies using various techniques of MADMs in combination with decision rules. Methods: The study is an applied research using multi-attribute decision making (MADM) methods. This study extracted the attributes related to health technology assessment from global literature and experts' opinions. In this study, two different types of experts were consulted: the first type, including three experts in the field of the decision-making techniques, on the subject of setting priority on health focusing on MADM; and the second one consists of seven experts in the field of HTA, asked about the selection of attributes and determination their importance. Candidate health technologies were individually weighted and ranked using TOPSIS, SAW and VIKOR by the weight and decision matrix. The results obtained from various techniques were combined and ranked using Copeland's technique to obtain the final ranking of health technologies. To determine HTA type reports, decision rules were defined. All models were designed via MS Excel. Results: This study chose eight technologies according to six tradeoff attributes. These attributes included health benefits at the population level, vulnerable population size, availability of alternative technologies, budget impact, financial protection, and quality of evidence. Their exact weights were 0.25, 0.121, 0.146, 0.132, 0.167 and 0.181, respectively. Also, safety and uncertainty about the cost-effectiveness were considered as the veto and decision rules respectively. Copeland's method was therefore used to combine the methods: Whereas HT2 (The technology for treating patients suffering from varicose) was ranked the highest priority and HT3 (The palliative method for patients who suffer from various cancers) was ranked the lowest (for preventing from any ethical issue, the exact name of each technology wasn't mentioned). Conclusion: Finally, in accordance with decision rules which are based on various conditions of "uncertainty about the cost-effectiveness", it is recommended that full health technology assessment report be performed on three technologies, rapid health technology assessment report be performed on four others, and, finally no prioritizing for health technology assessment be made on one of them.

Optimum DNA Extraction Methods for Edible Bird's Nest Identification Using Simple Additive Weighting Technique.

A simple additive weighting (SAW) technique was used to determine and compare the overall performance of five DNA extraction methods from conventional (SDS method) to commercial kits (Qiagen, Wizard, and NucleoSpin) for identifying origins of edible bird's nest (EBN) using end-point polymerase chain reaction (PCR). A hybrid method (SDS/Qiagen) which has been developed by combining the conventional SDS method with commercialised Qiagen was determined as the most suitable in terms of speed and cost-effectiveness. The determination of optimum extraction method was by the performances on efficiency and feasibility, extracted DNA concentration, purity, PCR amplifiability, handling time and safety of reagents used. The hybrid SDS/Qiagen method is less costly compared to the commercial kits and offered a more rapid alternative to the conventional SDS method with significant improvement in the yield, purity and PCR amplifiability. The developed hybrid SDS/Qiagen method provides a more practical alternative over the lengthy process using conventional method and expensive process using commercial kits. Using the simple additive weighting (SAW) technique and analysis, the Qiagen method is considered the most efficient and feasible method without consideration of cost as it yielded the purest extracted DNA and achieved the highest PCR amplifiability with the shortest turnaround time.

Importance rankings of nodes in the China Railway Express network under the Belt and Road Initiative.

China Railway Express (CR express) refers to the regular container trains transporting between China and European countries under the Belt and Road Initiative (BRI). This paper aims to conduct the systematic and in-depth research on the importance ranking of logistics nodes across the complex CR express network from China's national plan of the BRI perspective, with consideration of the connectivity between the 21st-Century Maritime Silk Road (MSR) and the Silk Road Economic Belt (SREB). In doing so, first, it sets up the complex network in the CR express transport. Second, based on the restraint coefficients in the theory of structural hole such as network scale, efficiency, grading and clustering co-efficiency, this paper applies the Multiple Attribute Decision Making (MADM) model in association with algorithm development in calculating the importance of the CR express nodes including both inland nodes and seaport nodes. The paper has three-fold contributions. In theory, it confirms the accuracy and practicability of the structural hole theory in the importance ranking of nodes in the complex network. In practice, it identifies important logistics nodes of CR express network across the BRI. Further, the findings in the paper contribute to optimising the structure of CR express transport and improving its network stability.

Some Interval-Valued Intuitionistic Fuzzy Dombi Heronian Mean Operators and their Application for Evaluating the Ecological Value of Forest Ecological Tourism Demonstration Areas.

With China's sustained economic development and constant increase in national income, Chinese nationals' tourism consumption rate increases. As a major Chinese economic development engine, the domestic tourism industry has entered a transition period operation pattern featured by diversified products. Among them, as a new hot spot of the tourism industry in China, ecological tourism has enjoyed rapid development, with great potential. Thus, the ecological value evaluation of forest ecological tourism demonstration areas is very important to the domestic tourism industry. In this paper, we propose some Dombi Heronian mean operators with interval-valued intuitionistic fuzzy numbers (IVIFNs). Then, two MADM (multiple attribute decision making) methods are proposed based on IVIFWDHM (interval-valued intuitionistic fuzzy weighted Dombi Heronian mean) and IVIFWDGHM (interval-valued intuitionistic weighted Dombi geometric Heronian mean) operators. Finally, we gave an experimental case for evaluating the ecological value of forest ecological tourism demonstration area to show the proposed decision methods.

Developing A Sustainable Urban-Environmental Quality Evaluation System in China Based on A Hybrid Model.

In China, with the acceleration of urbanization, people pay more attention to the quality of urban environment. Air pollution, vegetation destruction, water waste and pollution, and waste sorting have restricted the sustainable development of urban environment. It is important to evaluate the impact of these environmental concerns as a prerequisite to implement an effective urban environmental sustainability policy. The aim of this paper is to establish a system for evaluating sustainable urban environmental quality in China. We extracted six dimensions and 29 criteria for assessing urban sustainable environment. Then, a fuzzy technique and the best worst method were applied to obtain the weights for the dimensions and criteria. Next, grey possibility values were applied to evaluate the sustainable environmental quality of five cities: Beijing, Shanghai, Shenzhen, Guangzhou, and Hangzhou in China. A sensitivity analysis was performed to identify how the ranking of these five cities changed when varying the weights of each criterion. The results show that pollution control, the natural environment, and water management are the three most important dimensions for urban environmental quality evaluation. We suggest that controlling pollutant emissions, strengthening food waste management, improving clean production processes, and utilizing heat energy are the effective measures to improve the urban environment and achieve sustainable urban environmental development.

Assessment and improvement of wetlands environmental protection plans for achieving sustainable development.

Although wetland environmental protection plans are synonymous with wetland management and erosion control plans, the public perceptions of such plans often focus on their impact on the human enjoyment of wetland areas. These plans are affected by many interrelated influence factors, such as human welfare, property, safety, management, operations, maintenance, ecology, environment, artificial structures, climate control, and sustainable development. The purpose of this paper is to probe how to use qualitative and quantitative measurements of wetland environments to create plan indexes using criteria/attributes as well as how to help these indexes for achieving the aspiration levels in each criterion/attribute. Previous studies that attempted to measure environmental evaluations and plans have assumed that these criteria are independent, but this assumption does not hold in real-world applications of real problems. Therefore, in this proof-of-concept study, using an empirical exam among various attributes and to measure and evaluate the real conditions for improving the wetland environmental problems. A DEMATEL technique can be used to construct the INRM, the basic concept of an ANP was modified to determine the influential weights of criteria/dimensions in our research alternative, called DANP (DEMATEL-based ANP). Then we can construct a decision-making model via a hybrid modified VIKOR method to improve wetlands environmental management manager strategy formulation in performance evaluation toward for achieving the aspiration level. Using these techniques, a proposed model appeared, which can be used to explain interdependence and feedback problems. Based on the final results, we can also propose a gap improvement in the development of a sustainable development plan for the environment while taking comfort and safety into account to improve standards and achieve human welfare expectations.

An OWA Distance-Based, Single-Valued Neutrosophic Linguistic TOPSIS Approach for Green Supplier Evaluation and Selection in Low-Carbon Supply Chains.

This paper presents a technique based on the ordered weighted averaging (OWA) distance for the single-valued neutrosophic linguistic (SVNL) technique for order preference by similarity to an ideal solution (TOPSIS). First, the inadequacies of the existing SVNL TOPSIS are analyzed in detail. Second, a SVNL OWA distance (SVNLOWAD) measure is presented, and based on this, a modified TOPSIS, termed the SVNLOWAD-TOPSIS, is developed for multiple attribute decision-making problems with SVNL information. Third, a revised relative coefficient is proposed to rank potential alternatives. Finally, a numerical example concerning green supplier selection in low-carbon supply chains is introduced to demonstrate the effectiveness of the model.

Selecting an appropriate method to remove cyanide from the wastewater of Moteh gold mine using a mathematical approach.

The presence of cyanide ions in wastewater is dangerous to the health and life of living creatures, especially humans. Cyanide concentration should not exceed the acceptable limit in wastewaters to avoid their adverse effects to the environment. In this paper, in order to select the most appropriate method to remove cyanide from the wastewater of the Moteh gold mine, based on the experts' opinions, the use of calcium hypochlorite, sodium hypochlorite, and hydrogen peroxide was chosen as forerunning alternative in the form of a multi-stage model. Then, seven criteria including the amount of material consumed, ease of implementation, safety, ability to remove cyanide, pH, time, and cost of the process to assess the considered methods were determined. Afterwards, seven experts conducted numerous experiments to examine the conditions of each of these criteria. Then, by employing a mathematical method called "numerical taxonomy," the use of sodium hypochlorite was suggested as the best method to remove cyanide from the wastewater of the Moteh gold mine. Finally, the TOPSIS model was used to validate the proposed model, which led to the same results of the suggested method. Also, the results of employing taxonomic analysis and TOPSIS method suggested the use of sodium hypochlorite as the best method for cyanide removal from wastewater. In addition, according to the analysis of various experiments, conditions for complete removal of cyanide using sodium hypochlorite included concentration (8.64 g/L), pH (12.3), and temperature (12 °C).

Improving the food waste composting facilities site selection for sustainable development using a hybrid modified MADM model.

With the growth of population and the development of urbanization, waste management has always been a critical global issue. Recently, more and more countries have found that food waste constitutes the majority of municipal waste, if they are disposed of properly, will bring more benefits in sustainable development. Regarding the issue of selecting and improving the location to make the disposal facility towards achieving the aspiration level for sustainable development, since it involves multiple and complicated interaction factors about environment, society, and economy which have to be considered properly in the decision-making process of mutual influence relationship. It is basically a multiple attribute decision making (MADM) issue, a difficult problem which has been obsessing the governments of many countries is widely studied and discussed. This study uses the new hybrid modified MADM model, as follows, first to build an influential network relation map (INRM) via DEMATEL technique, next to confirm the influential weightings via DANP (DEMATEL-based ANP), and then to construct a decision-making model via a hybrid modified VIKOR method to improve and select the location for remaining the best disposal facilities. Finally, an empirical case study is illustrated to demonstrate that the proposed model can be effective and useful. In finding the process of decision making, environmental pollution is the main concern of many people in the area, but actually it is the resistance by the general public that has to be considered with first priority.

Data-Prefetching Scheme Based on Playback Delay and Positioning Satisfaction in Peer-To-Peer Video-On-Demand System.

As one of the most important applications in peer-to-peer (P2P) networks, the video-on-demand (VoD) system freely supports video cassette recorder (VCR) operation for users. However, the users may experience significant playback delay after frequent VCR operations in the VoD system, which will affect the quality of experience (QoE) of the users. Hence, selecting an appropriate data-prefetching strategy to support better VCR operation is an important approach to improve the QoE. This paper proposes a data-prefetching strategy (DSA) to determine the most suitable anchor interval by considering the playback delay and positioning satisfaction. According to the DSA, we use the multiple-attribute decision-making (MADM) theory to model the selection of intervals of prefetching data blocks (i.e., anchor interval) and the technique for ordering preference by similarity to an ideal solution (TOPSIS) algorithm to solve the MADM. The simulation results show that the DSA strategy obtains higher positioning satisfaction than the existing schemes, which is approximately 60% higher than the anchor points, popular parts of video, and user interests (API)-based method. Moreover, with the increase in network bandwidth, the DSA strategy can minimize the playback delay after VCR operation using relative few extra bandwidths.

An Entropy-Based Knowledge Measure for Atanassov's Intuitionistic Fuzzy Sets and Its Application to Multiple Attribute Decision Making.

As the complementary concept of intuitionistic fuzzy entropy, the knowledge measure of Atanassov's intuitionistic fuzzy sets (AIFSs) has attracted more attention and is still an open topic. The amount of knowledge is important to evaluate intuitionistic fuzzy information. An entropy-based knowledge measure for AIFSs is defined in this paper to quantify the knowledge amount conveyed by AIFSs. An intuitive analysis on the properties of the knowledge amount in AIFSs is put forward to facilitate the introduction of axiomatic definition of the knowledge measure. Then we propose a new knowledge measure based on the entropy-based divergence measure with respect for the difference between the membership degree, the non-membership degree, and the hesitancy degree. The properties of the new knowledge measure are investigated in a mathematical viewpoint. Several examples are applied to illustrate the performance of the new knowledge measure. Comparison with several existing entropy and knowledge measures indicates that the proposed knowledge has a greater ability in discriminating different AIFSs and it is robust in quantifying the knowledge amount of different AIFSs. Lastly, the new knowledge measure is applied to the problem of multiple attribute decision making (MADM) in an intuitionistic fuzzy environment. Two models are presented to determine attribute weights in the cases that information on attribute weights is partially known and completely unknown. After obtaining attribute weights, we develop a new method to solve intuitionistic fuzzy MADM problems. An example is employed to show the effectiveness of the new MADM method.

Intuitionistic Linguistic Multiple Attribute Decision-Making with Induced Aggregation Operator and Its Application to Low Carbon Supplier Selection.

The main focus of this paper is to investigate the multiple attribute decision making (MADM) method under intuitionistic linguistic (IL) environment, based on induced aggregation operators and analyze possibilities for its application in low carbon supplier selection. More specifically, a new aggregation operator, called intuitionistic linguistic weighted induced ordered weighted averaging (ILWIOWA), is introduced to facilitate the IL information. Some of its desired properties are explored. A further generalization of the ILWIOWA, called intuitionistic linguistic generalized weighted induced ordered weighted averaging (ILGWIOWA), operator is developed. Furthermore, by employing the proposed operators, a MADM approach based on intuitionistic linguistic information is presented. Finally, an illustrative example concerning low carbon supplier selection and comparative analyses are conducted to demonstrate the effectiveness and practicality of the proposed approach.