TOPSIS Analysis Research Articles

Optimization and prediction of additively manufactured PLA-PHA biodegradable polymer blend using TOPSIS and GA-ANN

Recent years have seen the proliferation of fused deposition modeling (FDM) as a means of manufacturing biodegradable products, for different applications such as rigid packaging, agricultural and biomedical. Blends of Polyhydroxyalkanoates (PHA) and polylactic acid (PLA) have been investigated to ascertain their prospective applications through FDM. This paper includes three parameters that affect the build process: layer height, nozzle temperature, and flow rate. 3D printed PLA/PHA can be characterized mechanically, and process parameters can be optimized to maximize design functionality. The experimental setup utilized a Taguchi L9 design, and TOSPIS was employed to optimize the output results. Using TOPSIS analysis, 0.2 mm layer thickness, 195 °C nozzle temperature, and 100 % flow rate were found to be the most optimal initiation parameters. The Taguchi analysis was used to analyze the output responses, and it was found that layer height had the greatest influence on mechanical properties, followed by flow rate and nozzle temperature. The percentage elongation at break has been improved significantly by adding PHA i.e., 170 % compared to PLA (5–10 %). This paper presents a framework for in-depth mechanical characterization of PLA-PHA 3D-printed parts, along with methods for optimizing process parameters to achieve optimal performance, as well as tools for modeling output responses using GA-ANN with an accuracy of 95 %.

Optimal Airport Selection for Iraq's Infrastructure Development: A TOPSIS Analysis

Optimal Airport Selection for Iraq's Infrastructure Development: A TOPSIS Analysis

Applying TOPSIS and AHP Intrinsic Properties to Explore Consumers’ Preferences for Public Ceramic Relief Murals in Taiwan Region

Ceramic mural art is a contemporary landscape art, carefully designed based on human nature, culture, and architectural wall space; combined with social customs, visual sensibility, and art. It may also become the main axis of ceramic art in the future. The most distinctive feature of Taiwan region’s public ceramic relief mural (PCRM) was pioneered by Pan-Hsiung Chu in 1987. In addition to breaking through the limitations of traditional PCRM, Chu uses local culture and perceptual art as themes, giving Taiwan region’s ceramic wall art a unique style and innovative value. This study uses in-depth interviews with experts to analyze the intrinsic properties of AHP. At the same time, IPA is used as the public’s preference evaluation, and TOPSIS analysis is applied to understand consumers’ preferences for PCRM design imagery. It is hoped that this will sort out the key preferences of consumers and provide a reference basis and research methods for promoting PCRM in the Taiwan region.

The impact on ecosystem services from rural revitalization activity in China Shandong Province, from a human well-being perspective of local residential

Rural decline is a global concern, and Ecosystem Services (ES) play a crucial role in both rural revitalization and the Human Well-being (HW) of residents. This study investigated 9 revitalization cases in Shandong province, China, employing both quantitative and qualitative methods. It confirmed the effect on HW based on ES, using a comprehensive assessment framework covering local ecosystem services contribution and economic/social effect derived from the Millennium Ecosystem Service Assessment (MA) and Japan Biodiversity Outlook (JBO) and consolidated variations into four ES dimensions from a HW perspective. As a result, 4 common types of rural revitalization were identified: (A) Large-scale Agriculture, (B) Local Specialty/Brand Making, (C) Industry Integration, and (D) Urbanization Village, based on actors, core industries, and key revitalization activities. According to interviews with local residents, the residents express high levels of satisfaction with revitalization activities. Using TOPSIS analysis, we found that urbanization-led revitalization (D) excels in “economic/social” dimensions but falls short in “Interaction with nature and health" and “Life and culture with nature." In contrast, agriculture-based revitalization activities (A and B) offer a more balanced impact across various ES dimensions. The well-being of residents varies depending on how they utilize and connect with nature. These findings underscore the potential of large-scale agricultural development to address rural population decline and suggest that fostering a positive exchange of ES, HW and capital between rural and urban areas can enhance the resilience of the rural-urban system. These insights are especially relevant for addressing the urban-rural imbalances in developing countries experiencing urban expansion and rural decline.

ESG-driven ecopreneur selection in European financial institutions: entropy and TOPSIS analysis

PurposeThis is the application of the Entropy and TOPSIS model to assess the eco-efficiency of European financial institutions using environmental, social, and governance (ESG) strategies. The aim is to categorize financial institutions based on key factors such as environmental training and management and to examine the alignment between ideal ESG performance and eco-efficiency.Design/methodology/approachThe study uses environmental, social, and governance (ESG) strategies to identify and categorize eco-entrepreneurs in European financial institutions. The study utilizes data to examine the structure between environmental training, effective management practices, and the green performance of financial institutions.FindingsThe study shows that European financial institutions exhibit varying degrees of eco-efficiency as assessed using the Entropy and TOPSIS model applied to ESG strategies. Surprisingly, the study found that institutions with a high ESG performance do not always match those with the highest eco-efficiency.Research limitations/implicationsThey emphasize the need for financial institutions to align their operations with sustainable practices. This research provides insights to increase eco-efficiency and improve the ESG performance of financial institutions. It also informs policy and decision-making in these institutions in relation to environmental training and management practices, contributing to the wider dialogue on sustainable finance.Originality/valueThis indicates a discrepancy between ESG ratings and actual eco-efficiency, emphasizing the need to reassess the ESG framework. The study findings are crucial for aligning financial institutions with sustainable practices and improving the effectiveness of the ESG framework, especially for institutions at the lower end of the eco-efficiency spectrum.

Single Polymer Composites: An Innovative Solution for Lower Limb Prosthetic Sockets

The demand for affordable prostheses, particularly in low- and middle-income countries (LMICs), is significant. Currently, the majority of prosthetic sockets are manufactured using monolithic thermoplastic polymers such as PP (polypropylene), which lack durability, strength, and exhibit creep. Alternatively, they are reinforced with consumptive thermoset resin and expensive composite fillers such as carbon, glass, or Kevlar fibres. However, there are unmet needs that amputees face in obtaining affordable prosthetic sockets, demanding a solution. This study utilises self-reinforced PET (polyethylene terephthalate), an affordable and sustainable composite material, to produce custom-made sockets. Advancing the development of a unique socket manufacturing technique employing a reusable vacuum bag and a purpose-built curing oven, we tested fabricated sockets for maximum strength. Subsequently, a prosthetic device was created and assessed for its performance during ambulation. The mechanical and structural strength of PET materials for sockets reached a maximum strength of 132 MPa and 5686 N. Findings indicate that the material has the potential to serve as a viable substitute for manufacturing functional sockets. Additionally, TOPSIS analysis was conducted to compare the performance index of sockets, considering decision criteria such as material cost, socket weight, and strength. The results showed that PET sockets outperformed other materials in affordability, durability, and strength. The methodology successfully fabricated complex-shaped patient sockets in under two hours. Additionally, walking tests demonstrated that amputees could perform daily activities without interruptions. This research makes significant progress towards realising affordable prostheses for LMICs, aiming to provide patient-specific affordable prostheses tailored for LMICs.

Environmentally Friendly Strategies for Recycling Agricultural Waste to Produce Renewable Energy: A Case Study of Durian Fruit

The increasing need for harvests, resources, and facilities is associated with significant biowaste production from agricultural processes. Although the waste is nutrient-rich, it may become refinement lands for ailment-triggering bacteria when not managed correctly. The waste can be transformed into raw materials for valuable crops or sources of environmentally friendly energy. Therefore, this study examined agricultural waste management strategies as Indonesia's sustainable renewable energy source. SWOT and TOPSIS methods were used to identify the optimal approach for advancing renewable energy in Riau Province, while multiple respondents participated in identifying critical criteria and evaluating each option. The results showed that based on SWOT analysis, the Strength–Opportunity (SO) factor favored using agricultural waste for renewable energy in Indonesia. Furthermore, TOPSIS analysis indicated that Alternative A2 (Bioethanol) had the most significant distance among the alternatives, with a weight of 0.825. Future studies are needed to provide more accurate results and improve the current understanding regarding the evolution of renewable energy in Indonesia. Additionally, in-depth investigations should prioritize increased consumer awareness of renewable consumption, higher producer productivity, and strengthened policies.

An Assessment of CO2 Capture Technologies towards Global Carbon Net Neutrality

Carbon dioxide, the leading contributor to anthropogenic climate change, is released mainly via fossil fuel combustion, mostly for energy generation. Carbon capture technologies are employed for reducing the emissions from existing huge point sources, along with capturing them from direct air, to reduce the existing concentration. This paper provides a quantitative analysis of the various subtypes of carbon capture technologies with the aim of providing an assessment of each from technological, social, geo-political, economic, and environmental perspectives. Since the emissions intensity and quantity, along with the social–political–economic conditions, vary in different geographic regions, prioritising and finding the right type of technology is critical for achieving ambitious net-zero targets. Four main types of carbon capture technology were analysed (adsorption, absorption, membrane, and cryogenic) under four scenarios depending on the jurisdiction. The Technique for Order of Preference by Similarity to Ideal Solution (also known as the TOPSIS method) was used to establish a quantitative ranking of each, where weightages were allocated according to the emissions status and economics of each depending on the jurisdiction. Furthermore, forecasting the trends for technology types vis à vis carbon neutral targets between 2040 and 2050 was carried out by applying regression analysis on existing data and the emissions footprint of major contributing countries. The study found the membrane score to be the highest in the TOPSIS analysis in three of the four scenarios analysed. However, absorption remains the most popular for post-combustion capture despite having the highest energy penalty per ton of CO2 capture. Overall, capture rates are well short of projections for carbon neutrality; the methodology put forward for prioritising and aligning appropriate technologies and the region-by-region analysis will help highlight to technocrats, governments, and policymakers the state of the art and how to best utilise them to mitigate carbon emissions—critical in achieving the net-zero goals set at various international agreements on climate change.

Ethical and clinical aspects of tooth whitening in adolescents

This study aimed to analyse the ethical aspects to be considered in the practice of tooth whitening in adolescents, with the aim of establishing a solid basis for clinical decision-making and ensuring the well-being of young patients. A systematic review of the scientific literature was carried out to identify relevant studies on tooth whitening in adolescents. Databases such as PubMed, Cochrane and LILACS were used, using MeSH terms and DeCS descriptors. The selected studies were evaluated based on predefined inclusion and exclusion criteria. Subsequently, the TOPSIS method was applied to analyse and rank the most important ethical aspects in clinical practice. The results of the review showed that, although tooth whitening in adolescents is technically possible, its use must be clinically justified and based on informed consent. Several key ethical aspects were identified, such as patient autonomy, protection of the minor's well-being and clinical justification. The TOPSIS analysis allowed these aspects to be prioritised and a hierarchy of importance to be established. The results of this study can serve as a guide for dental professionals, promoting ethical and safe clinical practice in the treatment of adolescents. Future research is recommended to further investigate the long-term impact of these treatments and develop specific clinical protocols for this population

Analysis of the coupling coordination of logistics development level and environmental support system in central China and its spatiotemporal evolution

Abstract This research examines the synchronized progression of regional logistics and environmental support systems in China’s central region. Utilizing a comprehensive evaluation index system, the study employs a combination of entropy methods, TOPSIS analysis, and coupling coordination modeling to assess the development levels of regional logistics and environmental support systems across six central provinces from 2011 to 2020. The analysis focuses on comprehensive scores, coupling coordination degrees, and spatiotemporal evolution characteristics. The results indicate a synergistic relationship between the two systems in the six central provinces, with both comprehensive scores and coupling coordination D values demonstrating consistent growth over time. The study reveals a coordinated and orderly developmental pattern in the coupling and coordination relationship between the six provinces and the two systems within the central region. The overall degree of coupling and coordination in the central region exhibits a well-coordinated status, with provinces ranked as follows: Henan > Anhui and Hubei > Hunan > Shanxi and Jiangxi. This ranking demonstrates a spatial characteristic of high coordination in the middle and lower coordination at both extremities. The research identifies the underdeveloped state of regional logistics as the primary limiting factor. From the notable findings, this study’s conclusions offer valuable insights for policy formulation regarding the coordinated development of regional logistics and environmental support systems in China’s central region.

Analyzing the Influence Factors of New Energy Vehicles on Traditional Energy Vehicle Industry in China Based on Entropy Weighted TOPSIS and Pearson Analysis

Analyzing the Influence Factors of New Energy Vehicles on Traditional Energy Vehicle Industry in China Based on Entropy Weighted TOPSIS and Pearson Analysis

Evaluation and Discussion on the Sustainable Development of Higher Education

Though the higher education system has great significance to a nation, compelling model to evaluate the higher education system is currently lacking. Due to changes in the social environment, such as the epidemic, countries’ requirements for the health and sustainability of the higher education system are gradually increasing. To assess this system, a thorough evaluation model is established by k-means cluster analysis and TOPSIS analysis. 15 indicators in 8 countries from the Global Competitiveness Report (2009-2019) are selected. In addition, we choose China to do the further analysis. Calculation results of factor analysis show that there are 5 indicators with greater influence among 15 indicators. It makes sense to increase the weights of these five indicators in China for more sustainable development.

A Two-Warehouse Lot Sizing Problem for Defective Items with a Completely Backlogged Shortage Under Limited Storage Capacity for Rented Warehouses

Determining an economic order quantity across inventory management is vital for any production or distribution company. There is an assumption in classical lot-sizing problems that the inventories are stored in a single warehouse with unlimited capacity. However, the mentioned assumption may be unrealistic, and in many markets, owned warehouses (OW) have limited capacity, therefore, in some cases, a rented warehouse (RW) is considered for storing goods to create more flexibility in terms of space capacity. In this study, we proposed a more realistic extension of a two-warehouse system, which intends to investigate an optimal EOQ considering limited storage for both OW and RW. This paper contributes to considering multiple RWs with limited capacity. For this purpose, a two-objective MINLP lot-sizing problem with a discreet period and finite time horizon is taken into account. The complexity of the model is to determine if there is a need to rent one or multiple warehouses regarding limited storage on OWs and RWs as well as budget restrictions to hire one or multiple warehouses. Also, all parameters are considered to be stochastic which means they follow a specific probability distribution. As the capacity of RWs and the total available budget to rent them are random parameters, the constraint on budget, as well as RW’s capacity in a period, can be formulated as chance constraints. Finally, four multi-objective decision-making methods namely Goal programming, Lp-Metric, Goal Attainment, and Augmented E-Constraint are utilized to solve the concerned problem. Then, the best method is chosen based on graphical, statistical, and TOPSIS analysis. Moreover, the Lagrangian Relaxation method is applied since solving this optimization model in large-size problems requires a considerable amount of time. In the end, the effect of changing the rates of three parameters on objective function values is evaluated through sensitivity analysis.

Enhancing mechanical properties of polycarbonate parts developed by fused filament fabrication using RSM‐TOPSIS hybrid approach

AbstractFused filament fabrication (FFF) is a high‐tech additive manufacturing technique with a wide range of applications, as it allows the production of functional parts with complex geometries in a reasonable time. Mechanical characteristics and dimensional accuracy must be estimated for the functional testing of products created with different polymeric materials. The mechanical characteristics and dimensional quality of manufactured parts are determined by several process variables. The purpose of this research is to determine the effect of four significant process variables (layer thickness, filament extrusion temperature, extrusion width, and printing speed) on the mechanical characteristics (tensile, three‐point bending, compression, Izod, and shear strengths) of FFF‐printed polycarbonate parts. Statistical models were created using the central composite rotatable design of the response surface methodology to demonstrate the relationship between the mechanical properties and the process factors. The accuracy of the developed models was assessed using ANOVA. TOPSIS analysis has been used to determine the optimal process conditions for achieving the optimum mechanical quality characteristics of FFF‐printed polycarbonate parts. The fractured and deformed surfaces of the test samples were examined using scanning electron microscopy.Highlights Effect of process variables on mechanical properties of FFF‐printed PC parts was analyzed. Quadratic models based on the CCRD design of RSM methodology have been developed. The models correlate the mechanical characteristics to the process variables. ANOVA was used to determine the developed model's adequacy. TOPSIS was used to optimize the process conditions.

A Research on Measuring the Impact of Olympic Games Based on MOIM Model

Due to the high cost of hosting, the Olympic Games have gone from being a "sweet pastry" to a "hot potato". To quantify the impact of the Olympic Games on the host country, the impact of the Olympic Games on the host country's economy, land use, satisfaction (athletes and spectators), travel, opportunities for future improvement, host city/country prestige, and environmental factors were considered in the selection of indicators, and the absolute and relative impact methods were used to classify these variables. In model building, the weights of the indicators were determined comprehensively by combining the subjective and objective methods of EWM-AHP to establish the Olympic Games Impact Metric (MOIM) measurement model. Finally, by constructing a functional relationship between the indicator variables and the degree of impact of the Olympic Games on the host country, TOPSIS analysis is applied to quantitatively measure the impact of the Olympic Games on the host country.

A Hybrid Model Using PCA and BP Neural Network for Time Series Prediction in Chinese Stock Market with TOPSIS Analysis

The stock price changes rapidly and is highly nonlinear in the financial market. One of the common concerns of many scholars and investors is how to accurately predict the stock price and the trend of rising and falling in a short time. Machine learning and deep learning techniques have found their place in financial institutions thanks to the ability of time series data prediction with high precision. However, the prediction accuracy of these models is still far from satisfactory. Most existing studies use original, single prediction algorithms that cannot overcome inherent limitations. This study proposes a hybrid model using principal component analysis (PCA) and backpropagation (BP) neural networks. The historical records of China Merchants Bank are used for data collection from 2015 to 2021. PCA preprocesses the original data to reduce the dimensionality and is then adopted by the BP neural network to predict the stock closing price of China Merchants Bank. We compare and analyze the PCA–BP model with three training algorithms, and the results indicate that the Bayesian regularization algorithm performs best. Besides, we perform the stock prediction using a traditional exponential smoothing approach. The experiment results show that the predicted stock closing price is close to the actual value, and the mean absolute percentage error can reach 0.0130, which is more significant than the traditional approach. Furthermore, A TOPSIS approach is utilized to evaluate the robustness of the proposed model. Finally, we demonstrate the usability of the designed hybrid model by predicting the stock price of another selected stock.

Experimental studies on mechanical properties of concrete by using artificial fine aggregate and as replacement of natural fine aggregate for sustainable development

Concrete is the second most used material on the earth after water. The current era of concrete making material like the coarse and fine aggregate need alternatives to overcome the demand. In this present study, artificial fine aggregate or artificial sand (AS) as an alternative to fine aggregate has been investigated. The parameters studied in this study to investigate the AS effect of concrete are slump, modulus of rapture, compression strength, split-tensile strength, and shear strength. The experimental results show that the fresh properties and compression strength show significant changes when the replacement dosage of natural fine aggregate or natural sand (NS) increases with AS. However, the other parameters, namely shear strength, tensile strength, modulus of rapture, and AS replacement, also positively impacted concrete. The multi-criteria decision-making technique was used to determine the prepared mixtures’ optimum mixture. Based on TOPSIS analysis, it is confirmed that the replacement of AS is 25% more effective. The study revealed that 100% NS replacement is also possible by AS, but a suitable admixture is required for workability.

Customer Relationship Management to Retain Customers with the Topsis Method

In the era of globalization, the increasingly rapid development of technological sophistication is an aspect that can be utilized to achieve convenience, including the flow of information. Each company has its own way of retaining customers. At the Metacom store, efforts to retain customers have not been carried out in an updated and online manner. Customer Relationship Management (CRM) is one way of retaining customers to fulfill this goal by combining CRM and TOPSIS methods. For this reason, customer data analysis was carried out at the Metacom store using the Topsis method, from 10 transaction data, 2 were recommended to be given a discount on the goods. The results of applying TOPSIS use ranking results from goods transaction results. This Topsis analysis can be used to change a CRM application, where this application is equipped with a sales information system as well as goods data collection (Cashier) and a sales application using the Topsis method with a combination of these two methods in the Metacom Store. From the processed data

Rethinking of the future sustainable paradigm roadmap for plastic waste management: A multi-nation scale outlook compendium

The myriad consumption of plastic regularly, environmental impact and health disquietude of humans are at high risk. Along the line, international cooperation on a global scale is epitomized to mitigate the environmental threats from plastic usage, not limited to implementing international cooperation strategies and policies. Here, this study aims to provide explicit insight into possible cooperation strategies between countries on the post-treatment and management of plastic. First, a thorough cradle-to-grave assessment in terms of economic, environmental, and energy requirements is conducted on the entire life cycle across different types of plastic polymers in 6 main countries, namely the United States of America, China, Germany, Japan, South Korea, and Malaysia. Subsequently, P-graph is introduced to identify the integrative plastic waste treatment scheme that minimizes the economic, environmental, and energy criteria (1000 sets of solutions are found). Furthermore, TOPSIS analysis is also being adapted to search for a propitious solution with optimal balance between the dominant configuration of economic, environmental, and energy nexus. The most sustainable configuration (i.e., integrated downcycle and reuse routes in a closed loop system except in South Korea, which proposed another alternative to treat the plastic waste using landfill given the cheaper cost) is reported with 4.08 × 108 USD/yr, 1.76× 108 kg CO2/yr, and 2.73 × 109 MJ/yr respectively. To attain a high precision result, Monte-Carlo simulation is introduced (10,000 attempts) to search for possible uncertainties, and lastly, a potential global plastic waste management scheme is proposed via the PESTLE approach.

Effect of driving distractions on driver mental workload in work zone’s warning area

Traffic accidents are common in advanced warning areas of a maintenance work zone. One of the reasons for the accident is that the complex driving environment of the warning area makes drivers need to change lanes and speed frequently. Another reason is that driving distractions shift the driver's mental workload and make the drivers unable to complete the driving task well. The paper aimed to examine the impact of visual and cognitive distractions on the driver’s mental workload, eye movements, and driving behaviour when driving in advanced warning areas of the maintenance work zones. Thirty-two participants (mean age = 23.97 years) participated in the experiment and completed 3 advanced warning area simulation scenes. The road initial speed limit of simulation scenes was different: 60 km/h, 80 km/h and 100 km/h. The drivers needed to pass three scenes under three types of distraction tasks (no task, visual task and cognitive task). Six indices were used to evaluate the effect of the advanced warning area and the distracting secondary tasks on the driver's mental workload: two related to eye movements, two related to driver behavior, and two related to the electroencephalogram. The TOPSIS analysis was used to solve the problem of multi-evaluation indices comparison, sorting and selection. The results show that the driver has higher vehicle control ability under the distraction-free task condition than in other scenes. Furthermore, the impact of visual distraction on drivers is more significant than that of cognitive distraction, suggesting more visual attention is required for drivers when passing the complex working zone.