ASSESSMENT OF SUSTAINABLE WASTEWATER TREATMENT TECHNOLOGIES USING INTERVAL-VALUED INTUITIONISTIC FUZZY DISTANCE MEASURE-BASED MAIRCA METHOD

Effective wastewater treatment has significant effects on saving water and preventing unnecessary water scarcity. An appropriate wastewater treatment technology (WWTT) brings economic benefits through reuse in different sectors and benefits the society and environment. This study aims to develop a decision-making framework for evaluating the sustainable WWTTs under interval-valued intuitionistic fuzzy set (IVIFS) environment. The proposed MCDM framework is divided into two stages. First, a new Hellinger distance measure is developed to determine the degree of difference between IVIFSs and also discussed its desirable characteristics. Second, an interval-valued intuitionistic fuzzy extension of multi-attribute ideal-real comparative analysis (MAIRCA) model is developed using the proposed Hellinger distance measure-based weighting tool. Further, the proposed model is implemented on an empirical study of sustainable WWTTs evaluation problem. Sensitivity and comparative studies are made. The results indicate that odor impacts, sludge production, maintenance and operation are the most effective sustainable factors and Microbial fuel cell (MFC) technology is the best WWTT followed by natural treatment methods

Assessment of the agriculture supply chain risks for investments of agricultural small and mediumsized enterprises (SMEs) using the decision support model

A key challenge in responding to the emerging challenges in agri-food supply chains is encouraging continued new investment. This is related to the recognition that agricultural production is often a lengthy process requiring ongoing investments that may not produce expected returns for a prolonged period, thereby being highly sensitive tomarket risks. Agricultural productions are generally susceptible to different serious risks such as crop diseases, weather conditions, and pest infections. Many practitioners in this domain, particularly small and medium-sized enterprises (SMEs), have shifted toward digitalization to address such problems. To help with this situation, the current paper develops an integrated decision-making framework, with the Pythagorean fuzzy sets (PFSs), the method for removal effects of criteria (MEREC), the ranksum (RS) and the gained and Lost dominance score (GLDS) termed as PF-MEREC-RS-GLDS approach. In this approach, the PF-MEREC-RS method is applied to compute the subjective and objective weights of the main risks to assess the agriculture supply chain for investments of SMEs, and the PF-GLDS model is used to assess the preferences of enterprises over different the main risks to assess of the agriculture supply chain for investments of SMEs. An empirical case study is taken to evaluate the main risks to assess the agriculture supply chain for SME investments. Also, comparison and sensitivity investigation are made to show the superiority of the developed framework

AN EXTENDED SINGLE-VALUED NEUTROSOPHIC AHP AND MULTIMOORA METHOD TO EVALUATE THE OPTIMAL TRAINING AIRCRAFT FOR FLIGHT TRAINING ORGANIZATIONS

Aircraft’s training is crucial for a flight training organization (FTO). Therefore, an important decision that these organizations should wisely consider the choice of aircraft to be bought among many alternatives. The criteria for evaluating the optimal training aircraft for FTOs are collected based on the survey approach. Single valued neutrosophic sets (SVNS) have the degree of truth, indeterminacy, and falsity membership functions and, as a special case, neutrosophic sets (NS) deal with inconsistent environments. In this regard, this study has extended a single-valued neutrosophic analytic hierarchy process (AHP) based on multi-objective optimization on the basis of ratio analysis plus a full multiplicative form (MULTIMOORA) to rank the training aircraft as the alternatives. Moreover, a sensitivity analysis is performed to demonstrate the stability of the developed method. Finally, a comparison between the results of the developed approach and the existing approaches for validating the developed approach is discussed. This analysis shows that the proposed approach is efficient and with the other methods

An intuitionistic fuzzy entropy-based gained and lost dominance score decision-making method to select and assess sustainable supplier selection

Sustainable supplier selection (SSS) is recognized as a prime aim in supply chain because of its impression on profitability, adorability, and agility of the organization. This work introduces a multi-phase intuitionistic fuzzy preference-based model with which decision experts are authorized to choose the suitable supplier using the sustainability "triple bottom line (TBL)" attributes. To solve this issue, an intuitionistic fuzzy gained and lost dominance score (IF-GLDS) approach is proposed using the developed IF-entropy. To make better use of experts' knowledge and fully represent the uncertain information, the evaluations of SSS are characterized in the form of intuitionistic fuzzy set (IFS). To better distinguish fuzziness of IFSs, new entropy for assessing criteria weights is proposed with the help of an improved score function. By considering the developed entropy and improved score function, a weight-determining process for considered criterion is presented. A case study concerning the iron and steel industry in India for assessing and ranking the SSS is taken to demonstrate the practicability of the developed model. The efficacy of the developed model is certified with the comparison by diverse extant models

A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse

Blockchain technology and metaverse advancements allow people to create virtual personalities and spend time online. Integrating public transportation into the metaverse could improve services and collect user data. This study introduces a hybrid decision-making framework for prioritizing sustainable public transportation in Metaverse under q-rung orthopair fuzzy set (q-ROFS) context. In this regard, firstly q-rung orthopair fuzzy (q-ROF) generalized Dombi weighted aggregation operators (AOs) and their characteristics are developed to aggregate the q-ROF information. Second, a q-ROF information-based method using the removal effects of criteria (MEREC) and stepwise weight assessment ratio analysis (SWARA) models are proposed to find the objective and subjective weights of criteria, respectively. Then, a combined weighting model is taken to determine the final weights of the criteria. Third, the weighted sum product (WISP) method is extended to q-ROFS context by considering the double normalization procedures, the proposed operators and integrated weighting model. This method has taken the advantages of two normalization processes and four utility measures that approve the effect of benefit and cost criteria by using weighted sum and weighted product models. Next, to demonstrate the practicality and effectiveness of the presented method, a case study of sustainable public transportation in metaverse is presented in the context of q-ROFSs. The findings of this study confirms that the proposed model can recommend more feasible performance while facing numerous influencing factors and input uncertainties, and thus, provides a wider range of application

Interval-Valued Pythagorean Fuzzy Similarity Measure-Based Complex Proportional Assessment Method for Waste-to-Energy Technology Selection

This study introduces an integrated decision-making methodology to choose the best “waste-to-energy (WTE)” technology for “municipal solid waste (MSW)” treatment under the “interval-valued Pythagorean fuzzy sets (IPFSs)”. In this line, first, a new similarity measure is developed for IPFSs. To show the utility of the developed similarity measure, a comparison is presented with some extant similarity measures. Next, a weighting procedure based on the presented similarity measures is proposed to obtain the criteria weight. Second, an integrated approach called the “interval-valued Pythagorean fuzzy-complex proportional assessment (IPF-COPRAS)” is introduced using the similarity measure, linear programming model and the “complex proportional assessment (COPRAS)” method. Furthermore, a case study of WTE technologies selection for MSW treatment is taken to illustrate the applicability and usefulness of the presented IPF-COPRAS method. The comparative study is made to show the strength and stability of the presented methodology. Based on the results, the most important criteria are “greenhouse gas (GHG)” emissions (P3), microbial inactivation efficacy (P7), air emissions avoidance (P9) and public acceptance (P10) with the weight/significance degrees of 0.200, 0.100, 0.100 and 0.100, respectively. The evaluation results show that the most appropriate WTE technology for MSW treatment is plasma arc gasification (H4) with a maximum utility degree of 0.717 followed by anaerobic digestion (H7) with a utility degree of 0.656 over various considered criteria, which will assist with reducing the amount of waste and GHG emissions and also minimize and maintain the costs of landfills

Enabling technologies challenges of green Internet of Things (IoT) towards sustainable development in the era of Industry 4.0

The extensive adoption of the Internet of Things (IoT) has increased the carbon footprint on a large scale across the globe. To handle this challenge, scholars and policymakers are making efforts to propose novel energy-efficient solutions to provide a desirable environment for green-IoT (G-IoT). Additionally, further research is required to analyze the G-IoT-related challenges to elucidate the difficulties of its implementation for researchers. Moreover, the GIoT requirements have been considered in different network levels, namely software, hardware, architecture, communication. To present a comprehensive framework to identify the challenges of G-IoT, a survey using literature review and expert’s opinion is carried. Total 23 challenges are taken to evaluate and implement G-IoT technologies towards sustainable development achievements (SDA). Consequently, this article aims to rank and evaluate the challenges to implement the G-IoT towards the SDA. An integrated approach is proposed with stepwise weight assessment ratio analysis (SWARA) and additive ratio assessment (ARAS) under Pythagorean fuzzy sets. As a result, an machine-to-machine (M2M) standardization protocol with a weight value of 0.0508 has the first rank, followed by adaptation to natural energy sources with a weight value of 0.0479, information security and privacy protection with a weight value of 0.0469, and internet protocol version-6 (IPv6) for low-end devices with weight 0.0467. To validate the proposed method, sensitivity analysis and comparison using existing methods have been conducted. First published online 30 March 202

Low-carbon tourism strategy evaluation and selection using interval-valued intuitionistic fuzzy additive ratio assessment approach based on similarity measures

Recently, the assessment and selection of most suitable low-carbon tourism strategy has gained an extensive consideration from sustainable perspectives. Owing to participation of multiple qualitative and quantitative attributes, the low-carbon tourism strategy (LCTS) selection process can be considered as multi-criteria decision-making (MCDM) problem. As uncertainty is usually occurred in LCTSs evaluation, the theory of interval-valued intuitionistic fuzzy sets (IVIFSs) has been established as more flexible and efficient tool to model the uncertain decision-making problems. The idea of the present study is to develop an extended method using additive ratio assessment (ARAS) framework and similarity measures in a way to find an effective solution to the decision-making problems using IVIFSs. The bases of the proposed method are the IVIFSs operators, some modifications in the traditional ARAS framework and a calculation procedure of the weights of the criteria. To calculate criterion weight, new similarity measures for IVIFSs are developed aiming at the achievement of more realistic weights. Also, a comparison is demonstrated to the currently used similarity measures in order to show the efficiency of the developed approach. To confirm that the developed IVIF-ARAS approach can be successfully employed to practical decision-making problems, a case study of LCTS selection problem is considered. The final results from the developed approach and the extant models are compared for the validation of the proposed approach in this study

Technological capabilities in the era of the digital economy for integration into cyber-physical systems and the IoT using decision-making approach

In the digital economy, innovators have to deal with the value-capture problem, which necessitates different capabilities. They need to be fully aware of the dynamics of platforms and ecosystems. Such capabilities are needed to enable technologies mainly focused on in the present study. The current digital economy (where businesses are experiencing a big shift from a traditional setting to a widely-digitalized setting) requires companies and enterprises to incorporate innovation into their performance. The present paper aims to offer a novel realm of modern technologies by recognizing the roles the technological capabilities could play in the digital economy regarding for integration of cyber-physical systems (CPS) and the Internet of Things (IoT) into the digital economy. This paper develops an integrated decision-making framework called the Pythagorean fuzzy (PF)- method based on the removal effects of criteria (MEREC)-rank sum (RS)-double normalization-based multiple aggregation (DNMA) model by combining the PF-MEREC-RS and PF-DNMA methods. In this framework, the PF-MEREC-RS method computes the subjective and objective weights of the technological capabilities of the digital economy for the integration of IoT and the CPS. The PF-DNMA method uses to obtain the firms’ preference order over various technological capabilities in the digital economy for integration of the IoT and the CPS. In addition, this paper involves an empirical case study evaluating the key technological capabilities in the digital economy for integration of the IoT and the CPS. Furthermore, comparison and sensitivity investigation are made to show the superiority of the developed framework