Multi-criteria food waste treatment method selection using single-valued neutrosophic-CRITIC-MULTIMOORA framework

Evaluation of food waste treatment techniques using the complex q-rung orthopair fuzzy generalized TODIM method with weighted power geometric operator

Food waste has received wide attention due to its hazardous environmental effects, such as soil, water, and air pollution. Evaluating food waste treatment techniques is imperative to realize environmental sustainability. This study proposes an integrated framework, the complex q-rung orthopair fuzzy-generalized TODIM (an acronym in Portuguese for interactive and multi-criteria decision-making) method with weighted power geometric operator, to assess the appropriate technique for food waste. The assessment of food waste treatment techniques can be divided into three phases: information processing, information fusion, and ranking alternatives. Firstly, the complex q-rung orthopair fuzzy set flexibly describes the information with periodic characteristics in the processing process with various parameters q. Then, the weighted power geometric operator is employed to calculate the weight of the expert and form the group evaluation matrix, in which the weight of each input rating depends upon the other input ratings. It can simulate the mutual support, multiplicative preferences, and interrelationship of experts. Next, the generalized TODIM method is employed to rank the food waste treatment techniques, considering experts' psychological characteristics and bounded behavior. Subsequently, a real-world application case examines the practicability of the proposed framework. Furthermore, the sensitivity analysis verifies the validity and stability of the presented framework. The comparative study highlights the effectiveness of this framework using the existing frameworks. According to the result, Anaerobic digestion (0.0043) has the highest priority among the considered alternatives, while Incineration (-0.0009) has the lowest.

Municipal solid waste management: Identification and analysis of technology selection criteria using Fuzzy Delphi and Fuzzy DEMATEL technique

Municipal solid waste management (MSWM) poses a considerable challenge to developing countries like Bangladesh because of the rising waste generation rates and lack of effective management practices such as illegal open dumping and informal waste collection. One of the crucial factors in the successful management of MSW is to select the appropriate technology which is a complex multi-criteria and laborious process. Despite the global emphasis on the importance of MSWM in the literature, there is a lack of studies conducted in developing countries that effectively identify and analyze the critical performance criteria for appropriate technology selection. This research aims to address this shortcoming by identifying, and prioritizing the selection criteria and finally investigating the inter-relationship between them and the degree to which they affect or are affected by one another. First, a thorough literature review and expert consultation were employed to determine a set of 21 key criteria using the Fuzzy Delphi method (FDM). Later, taking into account the imprecise and subjective nature of the DEMATEL method on human judgements, the Fuzzy DEMATEL technique was employed to investigate the cause-effect relationships among the identified criteria. The findings of the study demonstrated that 14 criteria were categorized as causal elements that have the most significant influence on the MSWM technology selection process and 7 criteria were categorized as effect. The selection of MSWM technology demands greater consideration of the top three ranked criteria, namely T4- Access to Technology (AT), T8- Feasibility (F), and the Ec6-Infrastructure requirements (IR). By identifying the pertinent criteria, structures and interrelationships, the outcome of the study can facilitate a better understanding of causal relationships among the criteria that require specific consideration from the decision-makers and allow them to select appropriate MSW management technology.

Sustainable supplier selection based on VIKOR with single-valued neutrosophic sets

Considering economic, environmental, and social issues, the sustainability of the supply chain has drawn considerable attention due to societal and environmental changes within the supply chain network. The strategic study of the entire supply chain process and maximizing an organization's competitive advantage depend heavily on supplier selection based on sustainable indicators. Selecting sustainable suppliers for the supply chain is challenging since it is a multi-criteria decision-making (MCDM) problem with significant uncertainty in the decision-making process. This study uses the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique and single-valued neutrosophic sets (SVNS) to deal with the challenge of choosing a sustainable supplier with insufficient information. This method reduces the influence of personal experience and preference on the final evaluation results and the problem of excessive individual regret caused by factor correlation and improves the consistency of evaluation results. Finally, the method's success and adaptability are demonstrated by sensitivity analysis and additional comparison analysis, and the benefits and drawbacks of the suggested framework are examined. Compared to other approaches, it can assist decision-makers in communicating fuzzy and uncertain information, offering a perspective and approach for MCDM in the face of such situations, and helping them select suppliers of high caliber and who practice sustainable business practices.

Assessment of healthcare waste treatment methods using an interval-valued intuitionistic fuzzy double normalization-based multiple aggregation approach

Healthcare waste management has been an extensively attractive topic recently since it is one of the key concerns regarding both environment and public health, predominantly in developing nations. The optimization of the treatment procedure for healthcare waste is indeed a complex "multi-criteria decision-making (MCDM)" problem that involves contradictory and interweaved critical criteria. To successfully handle this issue, this study extends the original method, named the "double normalization-based multi-aggregation (DNMA)" approach, with "interval-valued intuitionistic fuzzy sets (IVIFSs)" for decision-making problems taking criteria in terms of benefit or cost types. This method involves two target-based normalizations and three subordinate utility models. To estimate the criteria weights, we propose a new parametric divergence measure and discuss the feasibility of the developed divergence measure based on existing divergence measures for IVIFSs. Further, the developed framework is implemented to elucidate the "healthcare waste treatment (HCWT)" problem. The comparative and sensitivity analyses of the outcomes indicate that the proposed approach efficiently tackles the problem of HCWT selection. The outcomes show that steam sterilization (0.462) is the optimal one for HCWT. The prioritization options, obtained by presented approach, are dependable and suitable, which are steam sterilization ≻ microwave ≻ incineration ≻ landfilling.

An extended DNMA-based multi-criteria decision-making method and its application in the assessment of sustainable location for a lithium-ion batteries' manufacturing plant

Lithium-ion battery (LiB), a leading residual energy resource for electric vehicles (EVs), involves a market presenting exponential growth with increasing global impetus towards electric mobility. To promote the sustainability perspective of the EVs industry, this paper introduces a hybridized decision support system to select the suitable location for a LiB manufacturing plant. In this study, single-valued neutrosophic sets (SVNSs) are considered to diminish the vagueness in decision-making opinions and evade flawed plant location assessments. This study divided into four phases. First, to combine the single-valued neutrosophic information, some Archimedean-Dombi operators are developed with their outstanding characteristics. Second, an innovative utilization of the Method based on the Removal Effects of Criteria (MEREC) and Stepwise Weight Assessment Ratio Analysis (SWARA) is discussed to obtain objective, subjective and integrated weights of criteria assessment with the least subjectivity and biasedness. Third, the Double Normalization-based Multi-Aggregation (DNMA) method is developed to prioritize the location options. Fourth, an illustrative study offers decision-making strategies for choosing a suitable location for a LiB manufacturing plant in a real-world setting. Our outcomes specify that Bangalore (L ₂), with an overall utility degree (0.7579), is the best plant location for LiB manufacturing. The consistency and robustness of the presented methodology are discussed with the comparative study and sensitivity investigation. This is the first study in the current literature that has proposed an integrated methodology on SVNSs to select the best LiB manufacturing plant location by estimating both the objective and subjective weights of criteria and by considering ambiguous, inconsistent, and inexact manufacturing-based information.

Application of evidence reasoning algorithm and QUALIFLEX with single-valued neutrosophic set for MCDM

Multi-criteria decision-making methods often include attributes with uncertain nature in practical applications, single-valued neutrosophic set is an important approach to solve above problem. QUALIFLEX method is a traditional decision method that makes decision by comparing different permutations of alternatives. In this paper, QUALIFLEX method is developed to solve the MCDM problem with the element of decision matrix is the single-valued neutrosophic number. Besides, since the defects of the original QUALIFLEX method about fusing information of different attributes, this paper uses Dempster-Shafer theory of evidence to integrate the information about weight and alternatives. Finally, by comparing the result with other MCDM methods, we find that the new method can not only obtain reasonable results, but also explain the decision results by probability theory. This paper not only develops the traditional MCDM method, but also a meaningful attempt to apply AI algorithm in MCDM method.

A New Approach to the Viable Ranking of Zero-Carbon Construction Materials with Generalized Fuzzy Information

This paper aims to put forward an integrated decision approach, with generalized fuzzy information for the viable selection of zero- and low-carbon materials for construction. In countries such as India, the construction sector accounts for high pollution levels and high carbon emissions. To restore sustainability and eco-friendliness, the adoption of low-carbon materials for construction is essential and, owing to the multiple attributes associated with the selection, the problem is viewed as a multi-criteria decision-making problem. Earlier studies on material selection have faced certain issues, such as the following: (i) the modeling of uncertainty is an ordeal task; (ii) the flexibility given to experts during preference elicitation is lacking; (iii) the interactions among the criteria are not well captured; and (iv) a consideration of the criteria type is crucial for ranking. To alleviate these issues, the primary objective of this paper was to develop an integrated framework, with decision approaches for material selection in the construction sector that promote sustainability. To this end, generalized fuzzy information (GFI) was adopted as the preference style as it is both flexible and has the ability to model uncertainty from the following three dimensions: membership, non-membership, and hesitancy grades. Furthermore, the CRITIC approach was extended to the GFI context for calculating criteria weights objectively, by effectively capturing criteria interactions. Furthermore, the COPRAS technique was put forward with the GFI rating for ranking zero- and low-carbon construction materials, based on diverse attributes. The usefulness of the framework was demonstrated via a case example from India and the results showed that the design cost, the financial risk, safety, water pollution, and land contamination were the top five criteria, with blended cement, mud bricks, and bamboo as the top three material alternatives for zero- and low-carbon construction. Finally, a sensitivity analysis and a comparison with other methods revealed the theoretical positives of this framework’s robustness and consistency–but it also revealed some limitations of the proposed framework.

A Bibliometric Review on Decision Approaches for Clean Energy Systems under Uncertainty

This paper aims to provide a bibliometric review on the diverse decision approaches in uncertain contexts for clean energy system (CES) assessment. A total of 126 publications are analyzed. Previous reviews on CES have discussed several research questions on the decision methods and the applicability of evaluating CES, along with the factors associated with CESs. In the present study, we focus on the bibliometric aspect that attempts to address questions related to the prominence of authors, countries/regions that focus on the current theme, impact of journals, importance of articles in the research community, and so on. The window considered for the study is from 2018 to 2021, with the motive to extend the review process from the preceding works. A review model is presented to address the questions based on the literature evidence. The results infer that CESs are the most viable mode for sustainable development, and the use of decision approaches is apt for the assessment of CESs.

Internet of things challenges of sustainable supply chain management in the manufacturing sector using an integrated q-Rung Orthopair Fuzzy-CRITIC-VIKOR method

Purpose

The “Internet of Things (IoT)” is a platform for involving smart devices via the Internet at a worldwide scale. It supports the “supply chain (SC)” and “information and communication technology (ICT)” infrastructure to be well integrated into an organization and externally with customers and suppliers. The “sustainable supply chain (SSC)” is currently unavoidable if a company seeks to satisfy the aggressive change in its customers' requirements. Numerous studies have confirmed that manufacturing firms have to accelerate the shift of their focus toward sustainability and the implementation of novel technologies, such as IoT, to accomplish their organizational goals most effectively. Although the literature consists of many theoretical approaches to IoT and numerous studies that have extremely concentrated upon the IoT technology and its potential applications, it lacks research with a focus on the challenges that arise when applying IoT to the “sustainable supply chain management (SSCM)”.

Design/methodology/approach

The present study proposes an integrated framework using the “Criteria Importance Through Intercriteria Correlation (CRITIC)” and “VlseKriterijumska optimizcija I kaompromisno resenje in Serbian (VIKOR)” models and employs to evaluate the IoT challenges to implement the SSCM. For estimating the criteria weights, the CRITIC tool is utilized. The organization's prioritization is obtained by the VIKOR procedure, which delivers simple mathematical procedures with precise and consistent outcomes.

Findings

To exhibit the practicality of the introduced model, a case study is taken to evaluate the IoT challenges to implement the SSCM within the “q-Rung Orthopair Fuzzy Sets (q-ROFSs)” environment. Moreover, the authors exhibit a sensitivity investigation over given parameter values, examining the stability of developed approach. Finally, the authors draw attention to a comparison between developed q-ROF-CRITIC-VIKOR decision-making approach with an existing q-ROF-TOPSIS method to show its superiority and potency.

Originality/value

The outcome of the study lies in observing the top benefits of individual businesses, and their entire SSCs can be found by implementing IoT. This paper investigates the most important challenges that individual firms and entire SSCs might while applying IoT. It provides a deep insight regarding the effects of IoT upon SSCM and the issues every firm need to contemplate when it is to apply IoT solutions.