Objective Weights Of Criteria Research Articles

Analyzing New Quality Productive Forces in New Energy Vehicle Companies Based on a New Multi-Criteria Decision Analysis Model

Assessing the new quality productive forces (NQPF) of new energy vehicle (NEV) companies is crucial for promoting the sustainable development of the NEV industry. This paper systematically evaluated and analyzed the NQPF of Chinese listed NEV companies from 2018 to 2022 using a novel multi-criteria decision analysis (MCDA) model. To address limitations in traditional MCDA models, such as unbalanced weight distribution, insufficient ranking differentiation, and incomplete identification of key influencing factors, this study introduced a new model, IDOCRIW-PROBID (integrated determination of objective criteria weights—preference ranking on the basis of ideal-average distance). First, an evaluation index system tailored to NEV companies’ NQPF was developed. Then, the IDOCRIW method was used to objectively assign weights to the indicators, enhancing the scientific rigor of the weight distribution. The PROBID method was employed to rank companies based on their NQPF, identifying differences between them. Additionally, an obstacle degree model was introduced to analyze key influencing factors, compensating for the traditional MCDA model’s limitations in this regard. The results showed, first, that the proposed IDOCRIW-PROBID model has a high degree of consistency with the classical Entropy-TOPSIS (technique for order of preference by similarity to ideal solution) model in terms of ranking the results (correlation coefficient = 0.91), and that IDOCRIW-PROBID offers higher differentiation compared to other MCDA models, validating its reliability and superiority. Second, during the study period, the development levels of NQPF in Chinese listed NEV companies varied significantly, with most companies at a low level of development and showing a downward trend, indicating that companies face considerable challenges in improving their NQPF. Third, the obstacle degree analysis revealed that R&D lease fees, R&D depreciation and amortization, and direct R&D investment were the primary factors hindering NQPF growth. This research provides theoretical support and decision-making insights for strategic optimization in NEV companies and informs government policy formulation.

Impact of different parameters in tribological properties of enset ventricosum/ terminalia arjuna fibers /SiO2 filler incorporation

Natural fiber composites have garnered considerable interest in recent years as sustainable substitutes for synthetic materials, owing to their environmental advantages, including renewability, biodegradability, and cost-effectiveness. Notwithstanding these benefits, there is a vital need to improve the mechanical and tribological characteristics of these composites for applications involving significant wear. This work used compression molding to make hybrid composites with natural fibers (NFs) and nano silicon dioxide (nSiO2) filler. The matrix material was epoxy, and the natural reinforcements were Enset ventricosum (EV) and Terminalia arjuna (TA) fibers. Tensile (TS), flexural (FS), and impact (IS) characteristics improved using 1:1 SiO2 filler and EV/TA fiber reinforcement. The combination of 6 wt% SiO2 and 45 wt% EV/TA improved mechanical performance. A high SiO2 filler (6 wt%) in polymer-based composites decreased Specific Wear Rate (SWR), according to Taguchi optimization. A better fiber-matrix interaction improves the mechanical characteristics of materials with fillers. This study optimized several responses using the new combined compromise solution (CoCoSo) method. Multi-criteria decision making is used here. This study introduces Method based on the Removal Effects of Criteria (MEREC) to determine objective criteria weights. Conclusions from experiments show ideal results. CoCoSo's optimization study showed that Enset ventricosum and Terminalia arjuna fiber (EV/TA) hybridization affected composites' tribological behavior.This hybrid fiber combination carried the most influence, followed by fillers. The optimal results were obtained with 6 wt% SiO2/25 wt% EV/TA Hybrid fiber, 1000 m Sliding distance (SD), 2 m/s Sliding speed (SS), and 10 N axial load (AL).

An integrated method for shared power bank supplier selection based on linguistic hesitant fuzzy multi-criteria group decision making

With the increasing number of smartphone users, the potential of the shared power bank industry is increasing. The shared power bank supplier selection can be regarded as a multi-criteria group decision making (MCGDM) problem with linguistic hesitant fuzzy (LHF) sets (LHFSs). This paper proposes a linguistic hesitant fuzzy MCGDM method based on the MULITMOORA (Multi-Objective Optimization on basis of a Ratio Analysis plus the Full Multiplicative form), the BWM (best and worst method), and the prospect theory (PT). Firstly, a new comparison approach of LHFSs is proposed. We propose the LHF Bonferroni mean (BM), the LHF weighted BM and the LHF generalized weighted BM (LHFGWBM) operators. The decision makers’ weights are acquired via a tri-objective optimization model. This paper extends the BWM to obtain the subjective criteria weights and employs the entropy to acquire the objective criteria weights. The comprehensive criteria weights are generated by the Jenson-Shannon divergence. The LHFGWBM operator is used to generate the collective decision matrix. The comprehensive prospect value decision matrix is obtained. Then, we propose the PT-based MULTIMOORA method for LHF MCGDM. An example of shared power bank supplier selection is used to show the superiorities of the proposed LHF MCGDM method.

Centroidous Method for Determining Objective Weights

When using multi-criteria decision-making methods in applied problems, an important aspect is the determination of the criteria weights. These weights represent the degree of each criterion’s importance in a certain group. The process of determining weight coefficients from a dataset is described as an objective weighting method. The dataset considered here contains quantitative data representing measurements of the alternatives being compared, according to a previously determined system of criteria. The purpose of this study is to suggest a new method for determining objective criteria weights and estimating the proximity of the studied criteria to the centres of their groups. It is assumed that the closer a criterion is to the centre of the group, the more accurately it describes the entire group. The accuracy of the description of the entire group’s priorities is interpreted as the importance, and the higher the value, the more significant the weight of the criterion. The Centroidous method suggested here evaluates the importance of each criterion in relation to the centre of the entire group of criteria. The stability of the Centroidous method is examined in relation to the measures of Euclidean, Manhattan, and Chebyshev distances. By slightly modifying the data in the original normalised data matrix by 5% and 10% 100 and 10,000 times, stability is examined. A comparative analysis of the proposed Centroidous method obtained from the entropy, CRITIC, standard deviation, mean, and MEREC methods was performed. Three sets of data were generated for the comparative study of the methods, as follows: the mean value for alternatives with weak and strong differences and criteria with linear dependence. Additionally, an actual dataset from mobile phones was also used for the comparison.

What makes a better hotel selection? A hybrid approach considering tourists’ preference and review helpfulness

ABSTRACT Hotel selection is crucial in planning trips. Several studies constructed the decision methods, which assumed that people are completely rational and neglected decision-maker’s (DM’s) behavioural aspects, based on text reviews or numerical ratings with the subjective or objective weights of criteria. Therefore, this study proposes a picture fuzzy gained and lost dominance score (PF-GLDS) method based on prospect theory, which integrates user-generated text reviews and multi-criteria ratings to facilitate hotel selection while considering tourists’ preference and review helpfulness. First, review helpfulness is analyzed to enhance data quality. Second, a decision matrix is constructed by simultaneously considering sentiment in helpful text reviews as well as multi-criteria ratings. Third, the criteria are derived by the maximising deviation and best worst methods (BWM), respectively, for tourists’ preferred objective and subjective weights. Finally, to address hotel selection problems, an extended GLDS method with picture fuzzy information, considering bounded rationality behaviour, is developed. Empirical evaluation on five hotels from the TripAdvisor website demonstrates the reasonableness and advantages of our proposed hybrid approach in achieving more objective and reliable decision making. Concurrently, this study can serve as a reference for tourists seeking well-suited hotels and tourism website optimisation.

The selection of reform models for provincial rural credit cooperatives unions in China using an extended CPT-TODIM method based on novel type-2 fuzzy numbers

The selection of a suitable reform model for provincial rural credit cooperatives unions (PRCCUs) is a pivotal aspect of China’s ongoing financial reform endeavors. This involves optimizing internal processes, enhancing efficiency, minimizing operational costs, elevating service quality, strengthening financial innovation capabilities, and promoting the healthy growth of rural financial markets. However, current research on this matter primarily concentrates on qualitative analysis. As of yet, a scientifically grounded decision-making framework from a quantitative standpoint has not been developed. This absence of quantitative analysis results in inaccuracies in research findings, thereby hindering the practical applicability of outcomes. To tackle this formidable challenge, we propose an innovative quantitative analysis framework employing the multi-criteria group decision-making method. This framework, which builds upon the cumulative prospect theory (CPT), the TODIM method, and the most recent advances in type-2 fuzzy numbers (T2FNs), is referred to as the T2FNs-CPT-TODIM. Initially, we define a novel score function, followed by the introduction of a fresh method for computing the distance between the T2FNs. Subsequently, our model pioneers an exclusive weight allocation strategy for decision-makers, grounded in the principles of Dice Similarity. Furthermore, the objective weights of criteria can be computed utilizing the Distance Correlation-based CRITIC approach. We then optimize the rankings by applying the advantage of gains and losses preference in the CPT-TODIM. Ultimately, we apply our proposed model to the practical task of selecting the optimal reform model for a specific PRCCU. Thorough comprehensive sensitivity and comparative analyses, the results validate the theoretical robustness and practical efficacy of our proposed method.

Decision analysis with IDOCRIW-QUALIFLEX approach in the 2TLq-ROF environment: An application of accident prediction models in Pakistan

In Pakistan, the assessment of road safety measures within road safety management systems is commonly seen as the most deficient part. Accident prediction models are essential for road authorities, road designers, and road safety specialists. These models facilitate the examination of safety concerns, the identification of safety improvements, and the projection of the potential impact of these modifications in terms of collision reduction. In the context described above, the goal of this paper is to utilize the 2-tuple linguistic q-rung orthopair fuzzy set (2TLq-ROFS), a new and useful decision tool with a strong ability to address uncertain or imprecise information in practical decision-making processes. In addition, for dealing with the multi-attribute group decision-making problems in road safety management, this paper proposes a new 2TLq-ROF integrated determination of objective criteria weights (IDOCRIW)-the qualitative flexible multiple criteria (QUALIFLEX) decision analysis method with a weighted power average (WPA) operator based on the 2TLq-ROF numbers. The IDOCRIW method is used to calculate the weight of attributes and the QUALIFLEX method is used to rank the options. To show the viability and superiority of the proposed approach, we also perform a case study on the evaluation of accident prediction models in road safety management. Finally, the results of the experiments and comparisons with existing methods are used to explain the benefits and superiority of the suggested approach. The findings of this study show that the proposed approach is more practical and compatible with other existing approaches.

Development of Partition-Designed Outdoor Workwear with Optimal Fabric Selection

The necessity for anti-heat stress workwear to ensure the safety and performance of outdoor workers in hot, humid environments is clear. Yet, there is a gap in fabric selection techniques that consider multi-criteria decisions and account for the varying functional needs across different body regions. Here, we proposed a hybrid multi-criteria decision-making approach, merging the efficacy coefficient method, analytic hierarchy process, entropy weight, and technique of order preference by similarity to the ideal solution for developing ergonomic modular outdoor workwear. This method is tailored for anti-heat stress workwear, balancing competing functional demands. Initial research involved surveying workwear requirements in terms of human, clothing, and environmental factors, leading to the selection and testing of 15 fabrics for 6 partitioned designs. We established data standardization by the efficacy coefficient method and six evaluation index systems for human body requirements, with analytic hierarchy process and entropy methods determining subjective and objective criteria weights. The technique of order preference by similarity was used to produce the ideal solution then ranking of pre-screened fabrics, culminating in the optimal selection. For validation, three uniform prototypes were developed and tested through sweating manikin experiments and human wear trials to affirm the effectiveness of our approach. The partitioned design method proved more effective for anti-heat stress workwear for outdoor workers compared to existing solutions.

Integrated MCDM techniques for the selection of hybrid MWCNT/Ni–Zn–Fe nanocomposites for X-band radar absorption applications

In the 21st century, microwave-absorbing materials are used in a wide range of applications, such as in anechoic chambers and as electromagnetic interference shielding materials in radar and wireless communications. The design and development of new microwave-absorbing materials require substantial resources such as time, raw materials, and energy, and need to be cost-effective. Judicious selection of radar-absorbing materials from available alternatives often becomes difficult because it involves conflicting and non-commensurate attributes, such as bandwidth, reduced reflection loss, and thickness. This study aims to design and select novel double-layered multi-walled carbon nanotubes (MWCNT)/ Ni–Zn–Fe (NZF) microwave-absorbing materials using multi-criteria decision-making (MCDM) techniques such as TOPSIS, VIKOR, and PROMETHEE-II. Single-layered microwave-absorbing materials with various compositions of MWCNT and NZF were prepared using a low-cost and facilein-situpolymerization process. The multi-layered radar-absorbing materials reflection loss was determined using transmission line theory. Subjective and objective criteria weights from the analytical hierarchy process, entropy methods, and their calculated combined weights were utilized to implement the MCDM techniques. The combination of MWCNT/NZF radar-absorbing materials was chosen using integrated MCDM methods as the preferred microwave-absorbing material with a reflection loss of −15 dB for a 2.6 GHz bandwidth and a maximum reflection loss of –22 dB at 9.6 GHz in the X-band.

An integrated group decision making framework for business performance evaluation of performing arts enterprises with probabilistic hesitant fuzzy IDOCRIW-MOOSRA method

There is a lack of domestic and foreign research on the evaluation and improvement strategies of business performance of performing arts enterprises, especially in the context of the “restructuring” of cultural groups in China. Most of the existing studies are distributed in bulk, not only lacking in theoretical depth, but also lacking in systematization to a certain extent, which shows that the existing studies have not fully formed a mature and valuable theoretical system. The business performance evaluation of performing arts enterprises is a multiple attributes group decision making (MAGDM). This paper constructs a novel probabilistic hesitant fuzzy Multi-Objective Optimization Simple Ratio Analysis (PHF-MOOSRA) model based on the integrated determination of objective criteria weights (IDOCRIW) under the probabilistic hesitant fuzzy sets (PHFSs) for this issue. The PHFSs provides an evaluation circumstance containing more information which make the final decision-making results more accurately. Additionally, the IDOCRIW method separately and the MOOSRA method based on the MOORA method is proposed in PHFSs circumstance in this model. In the end, this model is then applied in a numerical case study for business performance evaluation of performing arts enterprises and compare this model with other existing methods.

Decision-theoretic rough set model and spatial analysis-based waste-to-energy incineration plant site selection: a case study in first-tier cities of China.

Selecting a sustainable waste-to-energy (WTE) incineration plant site is important for handling huge challenges created by on-going municipal solid waste. However, many studies with WTE incineration plant site problems fail to determine alternative evaluation criteria and cities beforehand, which may increase decision costs and evaluation risks. This paper proposes a novel methodology based on decision-theoretic rough set model and suitable analysis for selecting the optimal WTE incineration plant site. Firstly, from the features of cities, alternative evaluation criteria are determined by three-phase method. Considering different geographical features, a geographical index system is established. Secondly, subjective and objective criteria weights are determined by an improved DEMATEL (Decision Making Trial and Evaluation Laboratory) method and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method-based linear programming model under the hesitant fuzzy linguistic context, respectively. Subjective and objective criteria weights are combined to form the final criteria weights by building an optimization model. Thirdly, the decision-theoretic rough set model is utilized to select alternative WTE incineration plant sites. We utilize spatial analysis adopting Geographic Information System technology to rank all alternative cities to build facilities. Finally, a numerical case is performed to illustrate the feasibility of the proposed methodology. The sensitivity analysis with the parameter [Formula: see text] ranking from 0 to 1 is performed, the result confirms that the proposed methodology has better robustness. Compared with the multi-criteria decision-making methods, the effectiveness and superiority of the proposed methodology are demonstrated.

Optimal investment decision of agrivoltaic coupling energy storage project based on distributed linguistic trust and hybrid evaluation method

Photovoltaic (PV) power generation is becoming a good solution to meet energy demand. However, centralized PV production sites may pose a threat to industrial land or agricultural land. To solve the energy-environment-land conflict, agrivoltaic coupling energy storage (AVCES) projects become a feasible new land use model. The investment decision of AVCES project is a multi-criteria decision problem (MCDM). Therefore, this paper firstly constructs an evaluation index system containing four criteria: resources, economy, social, environment and ecology. Secondly, the subjective weights of each indicator are determined based on the distributed linguistic trust model and the cloud model, and the objective weights are determined based on the cloud model and the integrated determination of objective criteria weights (IDOCRIW) model. Subjective and objective weights are combined based on game theory. Finally, the TODIM model is used to get the optimal choice among multiple schemes. After the case study, the applicability and stability of the proposed framework are validated, and the research results will provide good reference values for the investment decision of AVCES projects.

Probabilistic double hierarchy linguistic risk analysis based on failure mode and effects analysis and S-ARAS method

Failure mode and effects analysis (FMEA) is regarded as useful and efficient tool in identifying and eliminating system failures and important means in safety and reliability analysis. It is widely utilized in diverse areas for improving and enhancing the performance of systems. However, in the procedure of risk assessment, traditional FMEA method usually ignores the influence of weights. Simultaneously, when represent risk assessment information, fuzzy and complex information cannot be represented accurately. Besides, psychological behaviors of decision-makers cannot be considered. Thus, this paper aims to present a new method based on FMEA and S-additive ratio assessment (S-ARAS) method to address the marine risk assessment problems under probabilistic double hierarchy linguistic (PDHL) environment. Firstly, the probabilistic double hierarchy linguistic term sets (PDHLTSs) are utilized to express the evaluation information of failure modes. The expert evaluation information of failure modes and subjective weight is also assessed by using PDHLTSs. The PDHLTSs can describe the information more reasonably and precisely. Secondly, FMEA method is used to evaluate these alternatives from three aspects of Severity (S), Occurrence (O) and Detection (D). Then, the bounded rationality of decision-makers (DMs) is considered. So, the prospect theory and ARAS method is combined to evaluate the risk problems. Meanwhile, comprehensive weight determination method is established based on the social network analysis (SNA) and The Integrated Determination of Objective CRIteria Weights (IDOCRIW) method under PDHL environment. The integrated method is more flexible in determining the importance of failure modes and avoids the randomness of subjective evaluation. Finally, the newly proposed method is applied to address the marine risk assessment problem. Sensitivity analysis of parameter and weight methods is carried out. Furthermore, comparison analysis is given to illustrate the superiority of the presented method.

A method for product appearance design evaluation based on heterogeneous data

The eye-tracking and electroencephalogram data, as physiological information, have been viewed as effective supplements to subjective reporting for guiding the product appearance design. In this context, how to combine heterogeneous information is a challenging question. This study proposes different methods to determine subjective and objective weights of criteria regarding the self-reporting, eye-tracking, and electroencephalogram data for the evaluation of product appearance design. We introduce the probabilistic linguistic term set with interval uncertainty (IUPLTS) to represent complex self-reporting data, and develop a method to aggregate IUPLTSs. An algorithm is proposed to fuse physiological data on the data layer and feature layer. To combine the obtained heterogeneous information, we define an objective weighting method that examines the differences in indicator data and the correlation between indicators, and then use a level difference maximization model to fuse subjective and objective weights. To ensure the stability of decision-making results for the problem involving a large number of indicators, we use the Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) to rank alternatives. An example regarding the evaluation of automobile appearance design schemes is presented to show the validity and practicality of the proposed method. The prototype support system of the proposed method has been developed and is freely available at https://github.com/BitSecret/DAQQSO.

A multi-criteria decision-making framework for distributed generation projects investment considering the risk of electricity market trading

Under the background of distributed generation (DG) participating in market trade, the scale of DG has developed rapidly. The investment decision of DG is actually a multi-criteria decision-making (MCDM) problem, nevertheless the current framework rarely considers the risk of market trading. Thus a framework containing scheme attributes and market risks needs to be established. Firstly, an index system including economic benefit, environmental and social benefit and market risk is established. Secondly, subjective and objective weight are combined by using game theory in weighting process. Among them, the subjective weight of each index is determined based on the plus-minus decision-making trial and evaluation laboratory model (plus-minus DEMATEL); the objective weight is determined by the combination of triangular intuitionistic fuzzy number (TIFN) and integrated determination of objective criteria weights (IDOCRIW) model. Finally, the TODIM model is used to rank the alternatives. Taking Shanghai as a case study, the robustness of the proposed framework is verified by sensitivity analysis and comparative analysis. The results show that the weights of index C34 is 0.12, indicating that market participants have a greater influence on market risk. The research will provide an effective tool for investment decision of DG in market trading.

Determining the effectiveness of countries in combating pandemics: COVID-19 case

The aim of this study is to develop a multidimensional integrated efficiency analysis (MDIEA) model to be implemented when a pandemic breaks out. The first phase of the model involved the determination of input and output criteria that might affect the course of combat against the pandemic. Two methods were employed in the second phase: the CRITIC method, which uses objective values to determine criteria weights; and, the Fuzzy SWARA method, which is based on subjective values and decision-makers opinions due to the assumption that the criteria might not be determined precisely and completely. The subjective and objective criteria weights obtained from these two methods were combined using the SOWIA method so that integrated criteria weights could be determined. In the third phase, three separate efficiency rankings were obtained using EATWOS, OCRA, and FDEA methods depending on the criteria weights. In the fourth phase, these efficiency rankings were combined by employing the TPOP method to obtain one single precise ranking. The previous studies mostly analyzed the efficiency of countries by using one single efficiency method, where, the model proposed in this study determines countries’ efficiency by employing three different efficiency analysis methods together; it makes use of different points of view and different calculation procedures of different methods. As another aspect, rural population ratio, diabetes prevalence rate, proportion of the population over 65 years old, number of intensive care beds and number of vaccine doses are study-specific criteria, unlike other studies. The present study is expected to contribute to the literature since it is the first study that proposes a model to evaluate the performances of countries during pandemics. The proposed model was implemented to assess OECD countries’ efficiency in their fight against COVID-19, which was a prevailing crisis worldwide. When all the obtained results are considered, it is difficult to claim that one single criterion is effective in combating the pandemic. For an effective fight against the pandemic, it is of great importance to keep the rate of infection and therefore the number of infected people under control. It is also possible for countries to change their policies or adopt stricter policies to contain the spread of the virus.

Multi‑criteria Analysis of the Competitiveness of Major Baltic Sea Container Terminals

The rapid growth in the volume of international container transport requires that the entire transport chain become more competitive, including maritime container terminals. The aim of the article is to identify the number and location of major Baltic container terminals and to perform a multi‑criteria analysis of the competitiveness of maritime container terminals in the Baltic Sea Region (BSR). In our study, we perform the AHP multi‑criteria analysis with subjective criteria weights, as well as the entropy method with objective criteria weights. Thus, we can evaluate the competitive advantages of each of the specified terminals in the region. We are among the first to study the competitiveness of individual maritime container terminals in the BSR. Thus, our research adds to the literature that has yielded results on the competitive advantage of the Baltic seaports.

Evaluate the drivers for digital transformation in higher education institutions in the era of industry 4.0 based on decision-making method

The digitalization of higher education (HE) institutions and relevant issues have attracted the attention of many educational stakeholders. ICT has become a subject of high importance in every context, particularly in the workplace; thus, a principal goal for universities and schools is to prepare future professionals capable of dealing with problems and searching for effective solutions by their digital competence as a key skill. In this regard, a new framework is developed to evaluate the main drivers of digital transformation in higher education institutions (HEIs) in the era of industry 4.0. The developed framework is proposed a decision approach that can effectively use the presented information to make decisions of high rationality. This framework is applied to compute the subjective and objective criteria weights, and it is used to assess the preferences of organizations. An empirical case study to evaluate the main drivers for the implementation of digital transformation in HEIs is taken. According to the findings, the most significant drivers for the implementation of digital transformation in HEIs in the era of Industry 4.0 are developing, updating, and adapting a curriculum (0.0425), integration of digital technologies for universal education (0.0420), and cloud computing (0.0419), respectively. Hence, the evaluation results also show that the option higher education institution (HEI)-4 has the highest overall utility degree (1.845) over different drivers for the implementation of digital transformation in HEIs in the era of Industry 4.0. Also, comparison and sensitivity investigation are made to show the superiority of the developed framework.

When content-centric networking meets multi-criteria group decision-making: Optimal cache placement policy achieved by MARCOS with q-rung orthopair fuzzy set pair analysis

Assessing the cache placement policy (CPP) is a crucial step in the deployment process of content-centric networking (CCN), which is still an open question. In this paper, assessing the CPP is formulated to be a multi-criteria group decision-making (MCGDM) issue since it involves the consideration of multiple experts, and a new aggregated MCGDM algorithm is presented for dealing with this issue. On that account, an assessment criteria system is to formulate to portray these experts’ considerations for assessing CPPs, and then the concepts of q-rung orthopair fuzzy set (q-ROFS) and set pair analysis (SPA) are presented to directly and indirectly define the group preference information of CPPs with respect to the criteria, respectively. Later, some revised aggregation operators are employed for aggregating the group preference information. Then, a new integrated objective criteria weights (IOCW) method based on score value and combined criteria weights based on non-linear comprehensive method are given for determining the important degrees of criteria. Based on IOCW method, non-linear comprehensive method, score function, distance measure, and aggregation operators, a new integrated q-rung orthopair fuzzy MCGDM model based on MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method is developed to rank CPPs. Finally, an example is given to illustrate the evaluation process of CPP, and the advantages of developed method are verified by comparative analysis.

An interval-valued neutrosophic based MAIRCA method for sustainable material selection

A plethora of Multi-Criteria Decision-Making (MCDM) methods is available for selecting an optimal material for a design problem with quantitative measurements. However, little research has been conducted on material selection methods in an interval neutrosophic environment to address uncertainty. In this research paper, a unique framework is presented that combines Interval-Valued Neutrosophic Sets (IVNSs) with the entropy–MultiAtributive Ideal-Real Comparative Analysis (MAIRCA) framework with the aim of simultaneously handling the objective criteria with crisp inputs and subjective criteria with ambiguous or uncertain information. To demonstrate the applicability of the proposed approach, a wing-spar of a Human-Powered Aircraft (HPA) is considered. At first, a panel of three subject experts makes judgments on the alternatives or criteria linguistically through IVNSs. Next, the skill level of each expert involved in the decision-making process is assessed using a novel weighting approach with linguistic information. After obtaining the objective criteria weights using the entropy weighting method, the performance of candidate materials for the HPA spar is evaluated using the MAIRCA method. The results indicate that S-glass70%-Epoxy Continuous Fibers, Ti-2Fe-3Al-10V and Al-7075 T6 are the top-ranked alternatives for spar application. The strong correlation of the proposed approach with other extant MCDM techniques demonstrates the reliability of the results obtained. In addition, the efficacy and practicality of the material selection tool is also validated with an outranking method in a simplified neutrosophic environment.