Literature analysis of the location selection studies related to the waste facilities within MCDM approaches.

The increase in waste and related environmental problems is one of the major problems compromising health and environmental quality in urban and rural areas. There are a number of policies that can be implemented to reduce waste, but since it cannot be completely eliminated, recycling and disposal facilities for waste will always be required. Researchers and professionals are currently grappling with the issue of where to locate waste facilities. In the light of all this information, a literature review is presented so that researchers can easily access and systematically review previous studies on the waste facility location selection problem. At this point, in order to reduce the reviewed studies to a reasonable level and to conduct a more organized research, this literature research has conducted within the framework of multi-criteria decision-making (MCDM) approaches, which is one of the most applied methods in location selection problems. The subsequent strengths, weaknesses, opportunities, and threats (SWOT) analysis delves into the strengths, weaknesses, opportunities, and threats in the field, offering a concise guide for future research in waste facility location selection problem. The SWOT analysis highlights the strengths of global environmental awareness and versatile MCDM approaches, while addressing weaknesses in emerging technology integration and potential biases. Opportunities for interdisciplinary collaboration and integration of sustainability metrics provide strategic pathways, but threats such as regulatory changes and limited funding underscore challenges. This analysis serves as a concise guide for future research in waste facility location selection.

Optimizing road safety: integrated analysis of motorized vehicle using lattice ordered complex linear diophantine fuzzy soft set.

In this manuscript, we delve into the realm of lattice ordered complex linear diophantine fuzzy soft set, which constitutes an invaluable extension to the existing Fuzzy set theories. Within this exploration, we investigate basic operations such as ⊕ and ⊗ , together with their properties and theorems. This manuscript is more amenable in two ways, i.e., it enables real-life problems involving parametrization tool and applications with an existing order between the components of the parameter set based on the preference in the complex frame of reference. Adaptive cruise control (ACC) is a system designed for maintaining distance between two vehicles and to sustain a manually provided input speed. The purpose of cars with ACC is to avoid a collision that frequently happens nowadays, thereby improving road safety regulations amidst rising collision rates. The fundamental aim of this manuscript is to prefer an applicable car with ACC together with its latest model by defining a peculiar postulation of lattice ordered complex linear diophantine fuzzy soft set ( L O C L D F S S ^ ) . Emphasizing real-life applicability, we illustrate the effectiveness and validity of our suggested methodology in tackling current automotive safety concerns, providing useful guidance on reducing challenges related to contemporary driving conditions.

Distance and similarity measures on belief and plausibility under q-rung orthopair fuzzy sets with applications.

Belief and plausibility functions based on evidence theory (ET) have been widely used in managing uncertainty. Various generalizations of ET to fuzzy sets (FSs) have been reported in the literature, but no generalization of ET to q-rung orthopair fuzzy sets (q-ROFSs) has been made yet. Therefore, this paper proposes a novel, simple, and intuitive approach to distance and similarity measures for q-ROFSs based on belief and plausibility functions within the framework of ET. This research addresses a significant research gap by introducing a comprehensive framework for handling uncertainty in q-ROFSs using ET. Furthermore, it acknowledges the limitations inherent in the current state of research, notably the absence of generalizations of ET to q-ROFSs and the challenges in extending belief and plausibility measures to certain aggregation operators and other generalizations including Hesitant fuzzy sets, Bipolar fuzzy sets, Fuzzy soft sets etc. Our contribution lies in the proposal of a novel approach to distance and similarity measures for q-ROFSs under ET, utilizing Orthopairian belief and plausibility intervals (OBPIs). We establish new similarity measures within the generalized ET framework and demonstrate the reasonability of our method through useful numerical examples. Additionally, we construct Orthopairian belief and plausibility GRA (OBP-GRA) for managing daily life complex issues, particularly in multicriteria decision-making scenarios. Numerical simulations and results confirm the usability and practical applicability of our proposed method in the framework of ET.

Decision support model for selecting construction and demolition waste management alternatives: A life cycle-based approach.

Construction and demolition waste (C&DW) represents a pressing concern within the European Union, underscoring the urgent need for effective waste management strategies. The selection of these solutions constitutes a complex task, entailing the identification of efficient C&DW management strategies that balance appropriate practices, regulatory compliance, resource conservation, economic feasibility, and environmental considerations. LCA is widely utilized to assess environmental impact, yet the economic aspect has not been adequately incorporated into the LCA process in the field of C&DW management. The life cycle costing (LCC) methodology has been tailored to assess economic performance in conjunction with LCA. The selection of an appropriate multi-criteria decision-making (MCDM) method is vital for the C&DW system. This study proposes a novel framework for C&DW management by integrating LCA and LCC outcomes into MCDM, using AHP for weight determination, and applying TOPSIS to identify the favorable alternative. Four waste management alternatives were examined in the Lombardy region of Italy, namely (i) landfill; (ii) recycling for concrete production and road construction, incineration with energy recovery; (iii) recycling for road construction; (iv) recycling for concrete production and road construction. We determine that, with the implementation of various scenarios, the most suitable scenario emerges to be recycled for concrete production and road construction, with a score of 0.711/1; recycling for road construction with final score 0.291/1, ranks second; recycling for concrete production and road construction, incineration with energy recovery scores 0.002/1, ranks third; and landfill (scores: 0/1) is the worst choice, signifying it has the highest environmental impacts and the least economic benefits. Lastly, recommendations were formulated to enhance the environmental performance of the system.

Using algorithmic game theory to improve supervised machine learning: A novel applicability approach in flood susceptibility mapping.

This study was carried out with the aim of applying Condorcet and Borda scoring algorithms based on Game Theory (GT) to determine flood points and Flood Susceptibility Mapping (FSM) based on Machine Learning Algorithms (MLA) including Random Forest (RF), Support Vector Regression (SVR), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in the Cheshmeh-Kileh watershed, Iran. Therefore, first, FS conditioning factors including Aspect (As), Elevation (El), Euclidean distance (Euc), Forest (F), NDVI, Precipitation (P), Plan Curvature (PlC), Profile Curvature (PrC), Residential (Re), Rangeland (Rl), Slope (Sl), Stream Power Index (SPI), Topographic Position Index (TPI), and Topographic Wetness Index (TWI) were quantified in each Sub-Watershed (SW). Based on this, flood and non-flood points were identified based on both GT algorithms. In the following, MLAs including Random Forest (RF), Support Vector Regression (SVR), Support Vector Machines (SVM), and K-Nearest Neighbors (KNN) were used for the distributional mapping of FS. Finally, based on optimal conjunct approaches, FS maps were presented in the study watershed. Based on the results, among the conjunct algorithms in FS classification, RF-Condorcet and RF-Borda models were selected as the most optimal MLA-GT hybrid models. The upstream SWs were highly susceptible. Also, the effectiveness of NDVI and forest conditioning factors in each classification approach was high. The similarity of SW prioritization based on Condorcet algorithm with RF-Condorcet algorithm was about 86.70%. Meanwhile, the degree of similarity in RF-Borda conjunct algorithm was around 73.33%. These results showed that Condorcet algorithm had an optimal classification compared to Borda scoring algorithm.

Psychological resilience factors in intensive care nursing: a hybrid multi-criteria decision-making model.

PURPOSE: To analyze the key factors influencing the psychological resilience of intensive care unit (ICU) nurses during the COVID-19 pandemic and put forward suggestions promoting resilience based on key improvement factors and clinical experience. METHODS: Data were collected from 35 ICU nurses in a hospital in Zhejiang Province, China, through a questionnaire survey conducted between January and February 2023. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was then used to construct and visualize the relationship structure between the factors. The DEMATEL-based Analytical Network Process (DANP) was applied to determine the influential weights of all factors. Finally, the key improvement factors were identified using importance-performance analysis (IPA). RESULTS: Based on the cause-effect impact network diagram (CEIND), it was concluded that (C 11), (C 22), and (C 32) are the key factors that promote the improvement of psychological resilience among ICU nurses. Additionally, these factors were the key factors that influence psychological resilience. The confidence levels of these results and the gap were 99.6% and 0.4%, respectively, which exceed the threshold value of 95%, indicating good stability. Finally, for the case hospitals, (C 13) was identified as the key improvement factor. CONCLUSIONS: Hospital administrators should support ICU nurses in enhancing their psychological resilience during major epidemics by: (i) Providing training on comprehensive protective measures and nursing skills; (ii) Effectively managing the human resources of nurses in the hospital to reduce their workload; (iii) Increasing social and organizational support for nurses to alleviate anxiety caused by large-scale public health events and improve their psychological resilience.

Navigating critical barriers for green bond markets using A fuzzy multi-criteria decision-making model: Case study in Vietnam.

As potent financial instruments channeling capital into climate and environmental projects, green bonds' issuance is frustrated by myriad obstacles. Therefore, this study aims to explore the critical barriers to green bond issuance in Vietnam. This study elucidates the salient barriers by utilizing an integrated multi-criteria decision-making methodology synthesizing the Fuzzy set theory-based Delphi, Decision-Making Trial and Evaluation Laboratory (DEMATEL), and DEMATEL-based Analytic Network Process (DANP). An extensive literature review of green bonds delineates five key dimensions related to impediments: Policy, Market, Financial, Capacity, and Awareness, with 38 discrete indicators representing potential obstacles. Firstly, employing a Fuzzy Delphi survey of 16 experts, 32 indicators are distilled for further analysis. Then, Fuzzy DEMATEL modeling evaluates the interrelationships and interactions among barriers. Finally, DANP is applied to obtain the relative importance of key barriers. Results unveil the five most formidable barriers as a weak regulatory framework and infrastructure (PO1), Limited availability of green bond issuance guidelines and templates (PO2), Insufficient incentives or tax benefits for green bond issuers (PO3), Limited coordination and alignment with international green bond standards (PO5), Lack of investor confidence in the quality and credibility of green projects (AW4), and Capacity constraints among issuers, particularly in smaller organisations or government agencies (CA1). The research contributes to the broader literature on green finance and offers valuable insights for promoting sustainable finance practices in Vietnam and other developing economies.

Numerical investigation on the impact of different design arrangements of helical heat exchangers with varying cross-sections utilizing ternary hybrid nanofluids.

Helical tube heat exchangers (HTHE) are commonly used as thermal devices in various thermal engineering applications. A comparative investigation was undertaken to examine several helical tube designs in relation to their potential uses with water and nanofluids. Additionally, employing the ternary hybrid nanofluid (THNF) flow in helical-type heat exchangers to assess the heat transfer and frictional loss is a unique concept, as there is currently no research on this specific application. This study involves analyzing three different design configurations, each of which has three different inlet profiles: round, square, and oval shapes. Hence, a numerical analysis has been conducted on nine cases, each including the same pipe length, helix diameter, and pitch distance. The specified range for the Reynolds number under the water and THNF flow condition is 5000-25000. The results are acquired for both fluids, considering the Nusselt number (Nu), friction factor (f), outlet temperature (T out ), and entropy production (S g ). Multi-Criteria Decision Making (MCDM) is employed to provide a thorough assessment of the overall performance of the proposed designs. The results have been shown as graphical representations, streamlines and contours where Nusselt number, friction factor and entropy generation have been evaluated. The Nusselt number has a higher value for the oval cross-section, while it reaches its lowest value for the square cross-section. The highest heat transfer rate is got for Design 1 with the oval-shaped case. The friction factor for a circular cross-section HHTE is 48 % higher than the friction factor for a square cross-section profile. In addition, the square shape at a Reynolds number (Re) of 25000 exhibits 5 % less entropy formation compared to the oval shape geometry at a Reynolds number of 5000. The results of MCDM analysis indicate that Design 1, which features a square section, exhibits superior performance. Conversely, Design 2, which incorporates a circular cross-section, demonstrates poor performance. Among the six ternary hybrid nanofluids, the Al2O3+CNT+Graphene nanofluid with a water basis exhibits the greatest Nusselt number.

A new integrated rough multi-criteria decision-making model for enterprise resource planning software selection.

Enterprise resource planning (ERP) is widely used to boost the total market power of businesses. The wrong selection is one of the key reasons why ERP installations fail. Due to the complexity of the business environment and the range of ERP systems, choosing an ERP system is a complex and time-consuming procedure. ERP alternatives may be assessed using several criteria, so the ERP selection process may be considered a multi-criteria decision-making (MCDM) problem. In this study, the rough best worst method (BWM) was used to determine criteria weights, while the newly developed rough integrated simple weighted sum product (WISP) was used to rank ERP alternatives. Results suggest that the SFT-4 coded software is regarded as the best option, followed by SFT-5, SFT-6, SFT-2, SFT-3, and SFT-1. Results of the newly developed rough WISP method are compared to those of existing rough techniques in the sensitivity analysis. The differences between them have been found to be negligible. The outcomes show how effectively developed rough BWM and WISP integrated method performs in terms of ERP selection with usability, accuracy, ease of use, and consistency. This study will help decision-makers in a context where ERP is implemented choose the best ERP software for different sectors.

Prioritizing Sustainable Denim Fabric through Integrated Decision-Making Framework.

In this study, a combined multi-criteria decision-making (MCDM) approach that integrates the logarithm methodology of additive weights (LMAW) and the double normalization-based multiple aggregation (DNMA) methods has been utilized to determine the optimal fabric structures considering the performance characteristics of denim fabrics containing recycled cotton. This approach focuses on sustainability and performance criteria, applying advanced decision-making methodologies to provide in-depth analysis and guidance for denim fabric selection. In this research, 15 distinct criteria were taken into account. Alternatives were ranked based on outcomes obtained from these methods. Although it was not anticipated that the top-ranked alternatives would simultaneously fulfill the beneficial or non-beneficial orientation of all criteria, an examination of the top three alternatives (A12, A5, and A15) for both garment groups revealed that they indeed aligned with the pre-determined criterion orientation. This highlights the effectiveness of the multi-criteria decision-making approach in the context of this study.

Digital twin and fuzzy framework for supply chain sustainability risk assessment and management in supplier selection.

Risks in the supply chain can damage many companies and organizations due to sustainability risk factors. This study evaluates the supply chain risk assessment and management and then selects the best supplier in a gas company in Egypt. A comprehensive methodology can use the experts' opinions who use the linguistic variables in the spherical fuzzy numbers (SFNs) to evaluate the criteria and suppliers in this study based on their views. Selecting the best supplier is a complex task due to various criteria related to supply chain risk assessment, such as supply risks, environmental risks, financial risks, regularity risks, political risk, ethical risks, and technology risks and their sub-criteria. This study suggested a new combined model with multi-criteria decision-making (MCDM) under a spherical fuzzy set (SFS) environment to overcome uncertainty and incomplete data in the assessment process. The MCDM methodology has two methods: the Entropy and COmbinative Distance-based Assessment (CODAS) methods. The SFS-Entropy is used to compute supply chain risk assessment and management criteria weights. The SFS-CODAS method is used to rank the supplier. The main results show that supply risks have the highest importance, followed by financial and environmental risks, and ethical risks have the lowest risk importance. The criteria weights were changed under sensitivity analysis to show the stability and validation of the results obtained from the suggested methodology. The comparative analysis is implemented with other MCDM methods named TOPSIS, VIKOR, MARCOS, COPRAS, WASPAS, and MULTIMOORA methods under the SFS environment. This study can help managers and organizations select the best supplier with the lowest sustainability risks.

Evaluating lecturer performance in Vietnam: An application of fuzzy AHP and fuzzy TOPSIS methods.

Higher education is regarded as being of paramount importance in Vietnam and as being essential to raising the level of the country's labor force and promoting economic progress. Evaluation of lecturers is one of the institution's activities and a crucial component of managing human resources in higher education institutions. How to evaluate faculty members' overall performance using a range of criteria is one of the key evaluation-related challenges. This study presents a method that uses fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to assess and rank the performance of lecturers. Specifically, the evaluation framework is developed by identifying criteria and sub-criteria based on a comprehensive review of existing literature. Following that, the fuzzy AHP approach is used to determine the weights of the criteria and sub-criteria using the pairwise comparisons. The Fuzzy TOPSIS approach is employed to assess and prioritize lecturers identified through expert evaluation. When applied in group decision-making, utilizing fuzzy AHP and fuzzy TOPSIS promotes agreement among decision-makers and diminishes uncertainty in decision-making processes. The utilization of the multiple criterion measurement approach can then be used to carry out the evaluation. The suggested framework is also demonstrated via a case study. The use of this framework can improve the evaluation's objectivity, accuracy, and scientific methodology. It is believed that this work will assist managers of higher education institutions improve their standards for educational quality.

Z-number based fuzzy MCDM models for analyzing non-traditional security threats to finance supply chains: A case study from Vietnam.

Non-traditional security (NTS) threats have a vast and profound impact on many aspects of economic, political, social, and many other areas, especially supply chain finance (SCF), particularly in countries like Vietnam, which potentially affects the economic efficiency of businesses' supply chain financial, thereby affecting the general economy of the country and the world. In order to prevent and minimize the negative impacts caused by NTS threats to SCF, this study was conducted to identify NTS threats affecting SCF in Vietnam, at the same time calculate the weight of the impact level and find out the cause and effect relationship between them. Solution strategies are also proposed and ranked, thereby serving as a reference basis for relevant parties to choose appropriate response solutions. Due to the multi-criteria nature of NTS threats, the multiple criteria decision-making (MCDM) method is used in combination with the Z-number concept and Fuzzy set theory to approach the problem of certainty and increase the accuracy of study. The NTS threats are first identified through a literature review and then validated for suitability using the DELPHI technique (DELPHI). Suitable threats will be determined by relationship, weighted by Decision Making Trial And Evaluation Laboratory (DEMATEL) method. Proposed strategies are ranked using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The results indicate that there are 19 NTS factors affecting SCF in Vietnam, and the global economic downturn, pandemic and health crisis, financial crisis and cybersecurity risk are the four root cause factors with the most decisive influence. Businesses and concerns need to prioritize addressing these four threats because they not only have a strong impact but also entail many other threats. The two strategies considered to be the most effective are a sustainable practice and a risk-hedging strategy. Businesses, governments, and stakeholders also should pay attention to the macroeconomic environment, technology, and environment and build sustainable businesses, regularly monitoring economic fluctuations and creating plans to prevent risks.

Evaluating future strategies for sustainable growth of fiberglass composites industry in developing countries: A novel hybrid SWOT-Fuzzy extended PIPRECIA approach.

The global fiberglass-composite market is expanding tremendously due to its extensive applications in the construction and automotive sector. The progress in low-medium income developing countries is slow. This study explores an exclusive hybrid model of SWOT (strengths, weaknesses, opportunities, and threats) analysis and Fuzzy extended PIPRECIA (pivot pairwise relative criteria importance assessment) to evaluate the strategies for sustainable development of fiberglass composites industry in Pakistan as a representative of low-medium developing countries. SWOT analysis is employed for examining the factors and sub-factors which have been extracted from a real-time industrial survey. While internal and external factors are also critically established to formulate a TOWS matrix comprising nine proposed strategies. Later the preferences as proposed by experts are evaluated by Fuzzy extended PIPRECIA i.e., a MCDM (multi-criteria decision making) model. Finally, SWOT factors, sub-factors and strategic choices are orderly ranked and presented. The results of the study reveal that development of a suitable environment to attract investors for the advancement and growth of the local fiber composites manufacturing industry (WO2 i.e., 0.175) is a most desirable and highly prioritized strategic choice. While maximizing environmental research to reduce environmental impact and better management of resources (WT2 i.e., 0.076) is the least favorable. The application of this exclusively developed MCDM model will provide an insight to the policy makers and assistive in strategic management and sustainable development of composite industry in developing countries. While this model can also be effective for other complex planning and decision-making processes.

Using CRITIC-TOPSIS and python to examine the effect of 1-Hepatnol on the performance and emission characteristics of CRDI CI engine with split injection.

Recently, biofuels with higher alcohol content have become a promising alternative to diesel fuel. These fuels are appealing because they are sustainable, renewable, and possess attractive fuel properties. This study uses a split injection strategy to analyze the performance and emissions of a CRDI diesel engine fueled by 1-heptanol. The work involved testing different fuel blends, ranging from 10 % to 30 %, while maintaining a constant engine speed of 1500 rpm and varying the operating load between 0 kg and 12 kg in 4 kg increments. During the second stage, the CRITIC-TOPSIS method determines the objective weights and rankings of various criteria and alternatives. A Python approach based on machine learning was used to ensure the CRITIC-TOPSIS results were accurate. Seven criteria were evaluated to maximize BTE while minimizing BSFC, NOx, smoke opacity, HC, CO, and CO2. The experimental results showed a slight drop of 2.98 % in BTE and an increase of about 13.33 % in BSFC. NOx and smoke opacity were reduced by 7.13%-4.53 %, while there was a 12.12 % increase in HC, 6.45 % higher CO, and a 5.5 % increase in CO2 at full load. Adding 1-heptanol to diesel and using a split injection strategy significantly reduced NOx and smoke opacity. The final ranking and best blend are determined using CRITIC-TOPSIS and Python algorithms to estimate performance and emissions criteria. At a load of 4 kg, D100 ranks first with a relative closeness value of 0.642, while at a pack of 8 kg, the blend HP20D80 ranks first with a relative closeness value of 0.633. According to the rankings, the HP20D80 blend is the best option for achieving optimal performance and reduced emissions in CRDI diesel engines. A research paper has presented a unique approach to multiple criteria decision-making (MCDM) validated using a Python algorithm. This method can assist decision-makers in making better-informed choices when faced with MCDM problems that involve various criteria and alternatives.

Intermodal travel planning and decision support integrated with transportation and energy systems.

The fast urbanization in China makes it all the more important to find sustainable solutions that are both comprehensive and energy-efficient. Because of its important role in lowering logistical expenses and pollutant emissions, intermodal transport is generally seen as an effective method of coordinating transportation operations, helping to address the growing economic and environmental issues. Considering the characteristics of a growing city, this article lays out a multi-criteria method for selecting which new initiatives for China's public transportation system should be prioritized. "Electric municipality bus," "light rail system," and "modernization to the current fleet and optimization" are the three enhancement initiatives that are outlined. Using transportation-related economic, social, and environmental sub-criteria, this research applies TOPSIS, an analytic hierarchy method and fuzzy approach for order preference by resemblance to ideal circumstance application, to prioritize transportation projects. The study aims to improve city life in Chongqing, China, by identifying the most environmentally friendly development projects. Applying the analytical hierarchy method (AHP), the relative importance of several sustainability criteria was established for use in making strategic decisions. The alternative projects for the given city have been ranked using the fuzzy TOPSIS approach. However, the investigated results show the supportive response of hybrid to environmental sustainability and vice versa for non-hybrid vehicles. However, the energy consumption in public transport remains a leading hurdle in sustainability across the three modes of transport: taxis, rail transit and buses. Finally, computer trains in public transport also surprisingly deal with environmental sustainability to keep the current & forthcoming generation from ecological harm. However, theoretical and empirical policy suggestions have been proposed to become clean & green shortly.

Comprehensive study on the selection and performance of the best electrode pair for electrocoagulation of textile wastewater using multi-criteria decision-making methods (TOPSIS, VIKOR and PROMETHEE II).

The accelerating environmental impact of the textile industry, especially in water management, requires efficient wastewater treatment strategies. This study examines the effectiveness of various electrode pairs in the Electrocoagulation (EC) process for treating textile wastewater, focusing on removing of Total Suspended Solids (TSS), turbidity, Chemical Oxygen Demand (COD), and Total Organic Carbon (TOC). A comprehensive analysis was conducted using thirty-six electrode pair combinations, consisting of six materials: Aluminium (Al), Zinc (Zn), Carbon (C), Copper (Cu), Mild Steel (MS), and Stainless Steel (SS). The results demonstrated that different electrode pairs yielded varying removal efficiencies for various pollutants, with the highest efficiencies being 92.09% for COD (Al-C pair), 99.66% for TSS (Al-Cu pair), 99.17% for turbidity (Al-MS pair), and 70.99% for TOC (SS-SS pair). However, no single electrode pair excelled in removing all pollutant categories. To address this, three Multi-Criteria Decision Making (MCDM) methods such as TOPSIS, VIKOR, and PROMETHEE II were used to assess the most effective electrode pair. The results indicated that the Al-Zn combination was the most efficient, exhibiting high removal efficiencies for various pollutants (99.32% for TSS, 98.88% for turbidity, 68.62% for COD, and 57.96% for TOC). This study demonstrates that the EC process can effectively treat textile effluent and emphasizes the importance of selecting suitable electrode materials. Furthermore, pollutant removal was optimal with the Al-Zn electrode pair, offering a balanced and efficient approach to textile wastewater treatment. Thus, MCDM methods offer a robust framework for assessing and optimizing electrode selection, providing valuable insights for sustainable environmental management practices.

Selection and Optimization of Carbon-Reinforced Polyether Ether Ketone Process Parameters in 3D Printing-A Rotating Component Application.

The selection of process parameters is crucial in 3D printing for product manufacturing. These parameters govern the operation of production machinery and influence the mechanical properties, production time, and other aspects of the final product. The optimal process parameter settings vary depending on the product and printing application. This study identifies the most suitable cluster of process parameters for producing rotating components, specifically impellers, using carbon-reinforced Polyether Ether Ketone (CF-PEEK) thermoplastic filament. A mathematical programming technique using a rating method was employed to select the appropriate process parameters. The research concludes that an infill density of 70%, a layer height of 0.15 mm, a printing speed of 60 mm/s, a platform temperature of 195 °C, an extruder temperature of 445 °C, and an extruder travel speed of 95 mm/s are optimal process parameters for manufacturing rotating components using carbon-reinforced PEEK material.

Evaluating the resilience of residential buildings during a pandemic with a sustainable construction approach.

The COVID-19 pandemic has been a catastrophic event that has affected all aspects of human life worldwide. Due to the high genetic mutations of the virus, there has been a prolonged search for definitive therapeutic discovery, leading to extended periods of home quarantine. As a result, homes have become multipurpose spaces for work, education, sports, and other daily activities. Given the importance of residential buildings as the first line of defense against possible future pandemics, a model has been proposed to assess their readiness to handle pandemics using a sustainable development approach. This study investigates the most crucial criteria for evaluating residential buildings and applies them in a Multi-Criteria Decision Making (MCDM) process. The final evaluation model is presented using the SWARA and COCOSO methods, along with a set of criteria selected and weighted by experts. The study shows that the criteria related to health and safety are more critical than other sectors. Buildings that meet the standards of this group better are likely to have a higher score.

Impact of Normalization on Entropy-Based Weights in Hellwig's Method: A Case Study on Evaluating Sustainable Development in the Education Area.

Determining criteria weights plays a crucial role in multi-criteria decision analyses. Entropy is a significant measure in information science, and several multi-criteria decision-making methods utilize the entropy weight method (EWM). In the literature, two approaches for determining the entropy weight method can be found. One involves normalization before calculating the entropy values, while the second does not. This paper investigates the normalization effect for entropy-based weights and Hellwig's method. To compare the influence of various normalization methods in both the EWM and Hellwig's method, a study evaluating the sustainable development of EU countries in the education area in the year 2021 was analyzed. The study used data from Eurostat related to European countries' realization of the SDG 4 goal. It is observed that vector normalization and sum normalization did not change the entropy-based weights. In the case study, the max-min normalization influenced EWM weights. At the same time, these weights had only a very weak impact on the final rankings of countries with respect to achieving the SDG 4 goal, as determined by Hellwig's method. The results are compared with the outcome obtained by Hellwig's method with equal weights. The simulation study was conducted by modifying Eurostat data to investigate how the different normalization relationships discovered among the criteria affect entropy-based weights and Hellwig's method results.