Weighted Aggregated Sum Product Assessment Research Articles

Hybrid Analysis of Road Service Level Determination Decision Support System

Traffic congestion on the highway is one of the problems often faced by road users, as on the highway traffic in the city of Padang often experiences congestion due to the growth of several highways that are relatively smaller than the growth of traffic volume, causing a decrease in road service levels. This study aimed to determine the level of road services in several traffic lanes in the city of Padang. Data analysis using Hybrid Decision Support System (HDSS) modeling by combining the Analytical Hierarchy Process (AHP) method with the Weighted Aggregated Sum Product Assessment (WASPAS) This method is included in the Multi-Criteria Decision Making (MCDM) group. The AHP method can consistently determine the weight value of each criterion, and the WASPAS method can analyze alternative data to obtain decision results by ranking with the Weighted Sum Model (WSM) and Weighted Product Model (WPM) processes. The ranking results show that there are three types of road services in the city of Padang, namely B, C, and D with an accuracy rate of 0.6947%, this the results of this study using HDSS modeling can provide a better analysis process.

Evaluating the efficiency of green innovation and marketing strategies for long-term sustainability in the context of Environmental labeling

In the contemporary landscape, as environmental concerns take center stage, consumers are increasingly urged to make ecologically friendly choices, facilitated by the prevalence of environmental labeling. This study undertakes a comprehensive investigation into the influence of environmental labeling on customer purchasing behavior, with a specific emphasis on evaluating the effectiveness of green marketing and innovation initiatives. Using the Fuzzy Analytical Hierarchy Process (AHP) and Fuzzy Weighted Aggregated Sum Product Assessment (WASPAS) methodologies, the research pinpoints the elements and tactics able to influence consumer behavior in connection to environmental labeling. Therefore, seven factors, twenty-one sub-factors, and six strategies are identified. The results of Fuzzy AHP show the prominent role of product attributes, marketing and promotion strategies, and sustainability practices while seeking to change consumer behavior with regard to environmental labeling. In addition, the findings from the Fuzzy WASPAS approach suggest that environmentally friendly packaging, product labeling, and partnerships and collaboration are the most successful green innovation and marketing strategies. The findings of this study can help shape the design of more effective environmental labeling programs and marketing plans for encouraging sustainable purchases.

Evaluation of disassembly line layouts using an integrated fermatean fuzzy decision-making methodology: An application for refrigerator disassembly line

The layout focusing on the physical arrangement of workstations is an important consideration when designing a disassembly line. The layout of a line has a significant impact on its efficiency. The new problem addressed within this study is evaluating the main disassembly line layout types with respect to a thorough hierarchy of evaluation criteria classifying quantitative and qualitative. The addressed problem is modeled as multi-criteria decision-making (MCDM). To this end, a novel methodology that combines Stepwise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) methods under the Fermatean fuzzy environment is proposed for sustainable waste management. Fermatean fuzzy SWARA (FF-SWARA) is used to find out the weight of criteria consisting of disassembly line balancing characteristics, reconfigurability, working conditions, and end-of-life product characteristics. Fermatean fuzzy WASPAS (FF-WASPAS) is used to rank the alternative disassembly line layouts consisting of straight, U-shaped, two-sided, and parallel lines considering the weight of criteria. The multi-objective mixed integer linear programming (MILP) model for the disassembly line balancing problem (DLBP) of each line layout type is integrated into the proposed methodology. This integration reflects the effect of balancing performance measurements such as the number of stations, removing hazardous parts early, removing high demand parts early, and line lead time. Reconfigurability principles, working conditions, and product characteristics that rely on expert opinions are considered under the qualitative criteria. The developed methodology was applied to a refrigerator disassembly line and verified by sensitivity analysis and comparative studies. The results show that the two-sided disassembly line layout is the best option.

Quintic fuzzy sets: A new class of fuzzy sets for solving multi-criteria decision-making problems under uncertainty

This study proposes a new class of fuzzy sets called Quintic Fuzzy Set (QuFS), where the sum of the fifth power of the membership degree and non-membership degree is less than or equal to one. We introduce the complement operator and basic operations on QuFS and further develop various theorems based on these fundamental set operations. We also present the standard modal operators on QuFS and discuss its elementary properties. We then define a novel score and accuracy function for ranking QuFS, as well as the Euclidean and Hamming distances between two QuFSs. A supplier selection example is presented in detail to illustrate the viability and utility of the proposed QuF-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. We also present a multi-criteria decision-making (MCDM) problem on COVID-19 lab selection to perform a comparative analysis of QuFS with Fermatean Fuzzy Set (FFS) and Pythagorean Fuzzy Set (PFS). Furthermore, we demonstrate an existing real case study on selection of Health care waste treatment (HCWT) technique in India and perform a comparative analysis with TOPSIS, SAW (Simple Additive Weighting) and WASPAS (Weighted Aggregated Sum Product Assessment) MCDM methods in QuF framework. With the advent of QuFS, a decision-maker can now employ the fuzzy notion to manage complicated and uncertain human judgements. The comparative results indicate that the suggested QuF measures and QuF MCDM technique outperform other fuzzy concepts regarding effectiveness and validity. Due to the restrictive nature of the current fuzzy set theories, the decision-makers in some complex, uncertain real-life problems are not free to choose the degree of membership and non-membership of their choice. Compared to the Intuitionistic Fuzzy Set (IFS), PFS, and FFS, the QuFS developed in this study has a bigger space grade space. This feature of QuFS enables decision-makers to structure complex, uncertain circumstances with greater flexibility in terms of membership and non-membership degrees.

Multiple-attribute group decision-making approach using power aggregation operators with CRITIC-WASPAS method under 2-dimensional linguistic intuitionistic fuzzy framework

The 2-dimensional linguistic intuitionistic fuzzy variables (2DLIFVs) provide an efficient tool to model the cognitive information of experts in practical circumstances while considering the reliability of the evaluation results. It is a hybrid model representing qualitative information, which derives from integrating the 2-dimensional linguistic variables (2DLVs) with linguistic intuitionistic fuzzy numbers (LIFNs). In this work, we first define a novel score function to establish a proper ranking order among the 2DLIFVs. Next, we define a new distance measure under a 2-dimensional linguistic intuitionistic fuzzy framework to determine the difference between 2DLIFVs. Some mathematical properties and special cases of the defined distance measure are also discussed. The power average (PA) operators provide aggregation tools, allowing aggregated arguments to support each other in the aggregation process. Motivated by the notion of power average (PA) and power geometric (PG), we define four new aggregation operators (AOs) to aggregate 2DLIFVs by considering information correlation in terms of support degree during the aggregation process. Several mathematical properties of the proposed AOs are also investigated. In addition, a new integrated 2DLIF-CRITIC-WASPAS methodology is developed in the 2-dimensional linguistic intuitionistic fuzzy environment to deal with complex decision issues. In this method, a “Criteria Importance Through Intercriteria Correlation (CRITIC)” approach is used to obtain the associate weights of the attributes, and the “Weighted Aggregated Sum Product Assessment (WASPAS)” method is executed to establish a valid ranking order among the alternatives.Moreover, a real problem of venture capital investment related to renewable energy projects is considered to demonstrate the applicability of the proposed methodology. The evaluation process considers four aspects: the management team, service or product, finance, and the market, which are related to 14 attributes. A sensitivity analysis is carried out to explain the reliability of the obtained results. Comparing the proposed method with some extant methods establishes the strength and robustness of the formulated method in real-world situations.

Evaluating airports' Sustainable Development Goals by using multi-criteria decision making methodologies.

The recent growth of the aviation industry, which poses significant environmental challenges, has heightened the pressure on the sustainability of airports. Airport sustainability requires a holistic approach that encompasses economic, social, environmental, and operational aspects. In this regard, the United Nations' 17 Sustainable Development Goals (SDGs) Agenda provides a roadmap for the aviation industry. However, despite recognizing the importance of SDGs, aviation authorities and airports often fail to effectively integrate them into their activities and annual reports. This study aims to evaluate the significance of SDGs for airports and select the airport that prioritizes SDGs the most using Multi-Criteria Decision Making (MCDM) methodologies. This study introduces a novel approach that integrates Step-wise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) methods, which are MCDM techniques, to enhance airport sustainability. The SWARA method is employed to evaluate and assign weights to the SDGs in the context of airports. SDG 8 holds the highest level of significance among the goals concerning airports, while SDG 14 falls outside the scope of airport sustainability aspects. Then, five international airports that have been designated as green airports by aviation authorities and assessment organizations are selected, and the optimal alternative is determined using the WASPAS method, considering the weights obtained through SWARA. Dallas/Fort Worth International Airport is the top choice due to its successful implementations and reports aligning with the SDGs.

Influence of defects formation on the cracking behavior of LPBFed Cu-Cr-Zr alloy: Micro-mechanism and CRITIC-WASPAS approach

Advanced strategies and techniques in the Laser Powder Bed Fusion (LPBF) process for printing Cu-Cr-Zr alloy must be created to overcome the major flaws such as cavity formation, unstable thermal capillary convection and thermodynamic instability. In this research, the significant process variables in the LPBF techniques such as Laser Power (LP) of 430, 500 and 570 W, Scanning Velocity (SV) of 550, 750 and 950 mm/s, Hatching Distance (HD) of 0.06, 0.08 and 0.10 mm were considered into account to fabricate a crack-free Cu alloy coupon with maximum Relative Density (RD), Ultimate Tensile Strength (UTS) and Reduced Elastic Modulus (REM). To optimize the process variables, a Criteria Importance Through Intercriteria Correlation (CRITIC) associated with the Weighted Aggregated Sum Product Assessment (WASPAS) approach was employed. Finally, the confirmation experiments were performed for the optimal settings (LP of 430 W, SV of 750 mm/s and HD of 0.06 mm) and the initial settings (LP of 570 W, SV of 550 mm/s and HD of 0.10 mm). The optimal settings show an 8.6 % enhancement in relative density of 99.82 %, which also reflects in 47 % improvement in UTS of 336 MPa and a 27.8 % enhancement in REM of 147.45 GPa compared with the initial settings. With the help of fracture morphology, the effect of defect development on the propagation of fractures on the printed coupons was also investigated. Moreover, the confirmation experiments aligned more with the CRITIC-integrated WASPAS approach.

Evaluation of the Contaminated Area Using an Integrated Multi-Attribute Decision-Making Method

Air pollution affects public health and the environment, creating great concern in developed and developing countries. In India, there are numerous reasons for air pollution, and festivals like Diwali also contribute to air contamination. Determining the polluted region using several air contaminants is significant and should be analyzed carefully. This study aims to analyze the air quality in Tamil Nadu, India, during the Diwali festival from 2019 to 2021, based on multiple air pollutants. The study models the impact of air pollution as a Multi-Attribute Decision-Making (MADM) problem. It introduces a hybrid approach, namely the Analytical Hierarchy Process-Entropy-VlseKriterijumska Optimizacija I Kompromisno Resenje (AHP-Entropy-VIKOR) model, to analyze and rank the areas based on the quality of air. A combined approach of AHP and entropy is employed to determine the weights of multiple air pollutants. The VIKOR approach ranks the areas and identifies the areas with the worst air quality during the festival. The proposed model is validated by performing the Spearman’s rank correlation with two existing MADM methods: Combinative Distance Based Assessment (CODAS) and Weighted Aggregates Sum Product Assessment (WASPAS). Sensitivity analysis is carried out to assess the effects of the priority weights and the dependency of the pollutants in ranking the regions. The highest air pollution level during the festival was seen in Cellisini Colony (2019), Rayapuram (2020), T. Nagar and Triplicane (2021) in their respective year. The results demonstrate the consistency and efficiency of the proposed approach.

Recommendation of Machine Learning Techniques for Software Effort Estimation using Multi-Criteria Decision Making

 For the development of the software industry, Software Effort Estimation (SEE) is one of the essential tasks. Project managers can overcome budget and time overrun issues by accurately estimating a software project's development effort in the software life cycle. In prior studies, a variety of machine learning methods for SEE modeling were applied. The outcomes for various performance or accuracy measures are inconclusive. Therefore, a mechanism for assessing machine learning approaches for SEE modeling in the context of several contradictory accuracy measures is desperately needed. This study addresses selecting the most appropriate machine learning technique for SEE modeling as a Multi-Criteria Decision Making (MCDM) problem. The machine learning techniques are selected through a novel approach based on MCDM. In the proposed approach, three MCDM methods- Weighted Aggregated Sum Product Assessment (WASPAS), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) were applied to determine the ranking of machine learning techniques on SEE performance based on multiple conflicting accuracy measures. For validating the proposed method, an experimental study was conducted over three SEE datasets using ten machine-learning techniques and six performance measures. Based on MCDM rankings, Random Forest, Support Vector Regression, and Kstar are recommended as the most appropriate machine learning techniques for SEE modeling. The results show how effectively the suggested MCDM-based approach can be used to recommend the appropriate machine learning technique for SEE modeling while considering various competing accuracy or performance measures altogether.

An identification of optimal waste disposal method for dumpsite remediation using the Fermatean fuzzy multi-criteria decision-making method.

Improperly managed wastes that have been dumped in landfills over the years pose various challenges, but they also offer potential benefits. The feasibility of recycling such waste depends on the type of wastes, the condition of dumpsites, and the technology implemented for disposal. The selection of an alternative waste disposal method from the many available options for dumpsite remediation is a complex decision-making process among experts. The primary aim of this study is to assist in an extended multi-criteria decision-making (MCDM) method to reduce complexity in the proposed dumpsite remediation problem influenced by multiple criteria and to identify the optimal waste disposal method. Data uncertainties are managed with the proposed Fermatean fuzzy preference scale, and the importance of all socio-economic criteria is assessed using the full consistency method (FUCOM). The final ranking results of the weighted aggregated sum product assessment (WASPAS) method identify that the Waste-to-Energy (WtE) process could play a significant role in the disposal of land-filled unprocessed wastes, promoting sustainable waste management. Meanwhile, the methodology explores the idea that financial and logistical constraints may limit the feasibility of large-scale recycling efforts. This combination of environmental science and decision science addresses real-world challenges, helping municipal solid waste management authorities implement sustainable waste management practices.

Decision Support System for Selection of Internet Services Providers using the ROC and WASPAS Approach

Along with the growth of the internet service provider industry, selecting an Internet Service Provider (ISP) has become an important decision to ensure optimal internet access. However, with so many ISP options available, consumers often face difficulties in choosing the service that best suits their needs. The aim of this research is to produce a decision support system that can help users choose the ISP that best suits their needs and preferences using the ROC (Rank Order Centroid) approach as a weighting technique and the WASPAS (Weighted Aggregated Sum Product Assessment) approach to determine the best alternative. The ROC approach is used to obtain criteria weights based on the ranking order of the importance of the criteria. On the other hand, the WASPAS method is used to determine the best alternative through weighted addition and multiplication, producing a final value that reflects the extent to which each alternative meets the specified criteria. The outcomes of the case study reveal a ranking of alternatives from highest to lowest scores, as follows: First Media (A2) achieving 0.8629, Indihome (A3) at 0.8416, MyRepublic (A5) with 0.7954, Biznet (A1) scoring 0.7844, and Oxygen (A4) at 0.7469. The usability testing yields an average score of 89%, suggesting that the system is apt for utilization, as it aligns with the functionalities users are seeking.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN VENDOR IT MAINTENANCE MENGGUNAKAN PENDEKATAN WASPAS

IT maintenance is important for a company because these activities are carried out to maintain and support the optimal performance of a company's IT systems and infrastructure. Generally, selecting an IT maintenance vendor is done by collecting vendor data and then evaluating it based on the desired criteria. This, of course, results in the time it takes to make a choice and makes it difficult to determine the best option. If you choose the wrong IT maintenance vendor, it will result in disrupting the company's stability. This research was conducted with the aim of developing a decision support system that can be used to determine the IT maintenance vendor that best suits their needs and preferences using the WASPAS (Weighted Aggregated Sum Product Assessment) approach. This method is used to determine the best option through weighted addition and multiplication, producing a final value that reflects the extent to which each option can meet the specified criteria. From the existing case studies, the best alternative was obtained, namely: Microsis (A4) got a preference value of 0.8769, followed by ICT Canopy (A1) with a preference value of 0.8613, Pillar IT (A2) with a preference value of 0.8408, Indocom Niaga (A5) with a preference value of 0.8180, and Sasana Digital (A3) with a preference value of 0.7389. The usability test carried out received a score of 88%, which indicates that the system is suitable for use.

Design modification and selection of improved stem design of the conical stem tibial implant for TAR using FE analysis and different MCDM methods.

The conical stem tibial design of total ankle replacement (TAR) has high implant-bone micromotion. This may lead to aseptic loosening which can be avoided by improving the tibial design. The objective was to propose the best stem design parameters to reduce implant-bone micromotion along with minimizing stress shielding using an integrated Finite Element-Multi Criteria Decision Making (FE-MCDM) approach. FE models of implanted tibia bones were prepared by changing the height of the stem, the diameter of the stem, and the slant of the stem. Weighted Aggregated Sum Product Assessment (WASPAS), Technique for Order of Preference by Similarities to Ideal Solution (TOPSIS), Evaluation based on Distance from Average Solution (EDAS), and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) MCDM techniques with equal weights for micromotion and stress shielding were considered. The micromotion and stress shielding were greater when the height of the stem was increased. Whereas, the increase in diameter and slant affected them marginally. The best-performing design was the Model with stem height 6 mm (diameter 6.4 mm and slant 4°) and after that was the Model with stem height 8 mm (diameter 6.4 mm and slant 4°), and then the Model with stem height 10 mm (diameter 6.4 mm and slant 4°). The height of the stem is the most important stem design parameter. Shorter height, moderate thickness, and moderate slanting stem designs are recommended.

Hamacher Maclaurin symmetric mean aggregation operators and WASPAS method for multiple criteria group decision making under [formula omitted] - spherical fuzzy environment

T-spherical fuzzy sets can accurately represent fuzzy information and effectively simulate real-world decision making scenarios by adjusting the parameter t. The Maclaurin symmetric mean can combine multiple arguments by considering the relationships between them in any decision making process. The main goal of this paper is to develop Maclaurin symmetric mean aggregation operators based on the Hamacher operations of T-spherical fuzzy sets. The developed operators are thoroughly examined through their fundamental properties. The defined operators are adopted to develop a decision making methodology called WASPAS (Weighted Aggregated Sum Product ASsessment) for solving multiple criteria group decision making problems in a T-spherical fuzzy environment. A real-life example of project assessment is illustrated to demonstrate the practicality of the proposed decision making approach. Sensitivity analysis of the parameters is carried out to check their effect on the decision results. A comparison analysis with existing methods confirms the accessibility of the developed approach.

Integrated Spherical Decision-Making Model for Managing Climate Change Risks in Africa

Decision-makers, researchers, practitioners, and stakeholders often struggle with selecting and prioritizing strategies to manage climate change risks. While recent research extensively explores this issue, the emphasis has largely been on regions other than Africa. This is significant, considering Africa’s anticipated exposure to various and severe impacts of climate change. This study applied a two-stage model that integrates the Step-Wise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) methods within a unique framework under the influence of spherical fuzzy (SF) conditions. In the initial stage, SF-SWARA determines the relative importance of the criteria, while the subsequent stage involves the SF-WASPAS method to rank the strategies. While the most critical challenges are limited access to finance and inadequacies in climate data, scenarios, and impact models, the solution to be considered is the promotion of a well-coordinated capacity-building programme. Furthermore, a comprehensive sensitivity analysis was conducted to validate the applicability of the proposed model. This research not only identifies and explains the challenges associated with climate change risks management in the African context but also significantly contributes to the body of knowledge by outlining and prioritizing the strategies required to address these challenges.

A NEW METHODOLOGY FOR TREATING PROBLEMS IN THE FIELD OF TRAFFIC SAFETY: CASE STUDY OF LIBYAN CITIES

Traffic safety is an area of great importance, since there are many traffic accidents every day in which a significant number of people are killed. Defining certain strategies and identifying potentially the most dangerous towns and cities regarding this area are, on the one hand, a necessity, and, on the other hand, a challenge. In this paper, integrated Multi-Criteria Decision-Making (MCDM) model for ranking cities in Libya from the aspect of traffic safety has been proposed. The model implies a set of 8 criteria on the basis of which 5 decision-makers rated the 10 most deprived cities in Libya. The Full Consistency Model (FUCOM) in combination with the rough Dombi aggregator is used to determine the significance of the criteria. The Rough Simple Additive Weighting (R-SAW) method is used to rank the alternatives. The rough Dombi aggregator is also used for averaging in group decision-making while evaluating the alternatives. The stability of the model and the obtained results has been verified by the sensitivity analysis, which implies a 2-phase procedure. In the 1st phase, rough Additive Ratio Assessment (R-ARAS), Rough Weighted Aggregated Sum Product Assessment (R-WASPAS), Rough Complex Proportional Assessment (R-COPRAS) and Rough Multi-Attributive Border Approximation-area Comparison (R-MABAC) methods are applied. The 2nd phase implies changing the parameter ρ in the procedure of rough Dombi aggregator, while the 3rd phase includes the calculation of Spearman’s Correlation Coefficient (SCC) that shows a high correlation of ranks.

Version [1.1]- [pyFDM: A python library for uncertainty decision analysis methods

This paper describes an extension of the pyFDM library by extending the functionalities of the programming package with new Fuzzy Multi-Criteria Decision Analysis methods such as Combined Compromise Solution (CoCoSo), Stable Preference Ordering Towards Ideal Solution (SPOTIS), Weighted Aggregated Sum Product ASSessment (WASPAS), Weighted Product Model (WPM), and Weighted Sum Model (WSM). Furthermore, the proposed update includes new normalization techniques, new distance metrics, and defuzzification methods to allow users to examine the greater variety of research approaches in a Triangular Fuzzy environment. Furthermore, the update also extends with the implementations allowing for fuzzy calculations outside the multi-criteria field, which is allowed by the implementation of selected mathematical operations for Triangular Fuzzy Numbers. The opportunity to visualize the data within the fuzzy extension considered is also included. The extension of the pyFDM package broadens the scope of its usage in research approaches, making it a more suitable tool for multi-criteria decision analysis within the fuzzy environment.

Entropy weighted WASPAS and MACBETH approaches for optimizing the performance of solar water heating system

In this work, multi-criteria decision-making (MCDM) techniques namely the weighted aggregated sum product assessment (WASPAS) method and the measuring attractiveness by a categorical based evaluation technique (MACBETH) are applied for predicting the optimum performance of a solar water heating system (SWHS) equipped with perforated delta-shaped obstacles. In total fifteen SWHS design alternatives based on the variation of pitch ratio (0.5, 1, 1.5, 2.0), angle of attack (15°, 30°, 45°), and Reynolds number (400, 800, 1200) were selected. The Nusselt number, friction factor, and thermohydraulic efficiency were fixed as the selection criteria in evaluating SWHS alternatives. By the entropy method, the importance of the identified criteria is quantified as weight, whereas the ranking of SWHS alternatives is determined by the WASPAS and MACBETH methods. The results show that the SWHS design alternative with a Reynolds number of 1200, pitch ratio of 1, and 45° angle of attack exhibits the optimal performance in selected criteria. Sensitivity analysis was used to demonstrate the robustness of the acquired ranking findings, which were further, validated using ten popular decision-making models.

Influences of social media in travel decision making

. This paper examines the considerable impact of social media on the decision-making processes related to travel. As social media platforms continue to expand rapidly, individuals gain access to a vast range of user-generated content and peer recommendations that significantly shape their travel choices. The study aims to explore how social media platforms influence perceptions, preferences, and decisions regarding travel. It investigates the ways in which platforms like Instagram, Facebook, Twitter, and travel-specific review sites are utilized by travelers to gather information, share experiences, and connect with others. Additionally, the study looks into the influence of social media personalities, such as influencers and content creators, in shaping travel aspirations and choices. The interactive nature of social media, with features that allow users to seek real-time advice and engage with travel-related content, adds immediacy and personalization to the decision-making process. This research on the role of social media in travel decision-making is vital for various stakeholders, including travelers, the travel industry, and researchers. Understanding this impact enables travelers to make more informed choices by helping them navigate the extensive range of available travel information, aligning their decisions with personal preferences and interests. Insights from this research can assist travelers in enhancing their planning processes by identifying trustworthy information sources, obtaining real-time recommendations, and effectively engaging with social media content and communities to improve their travel experiences. By applying the "Weighted Aggregated Sum Product Assessment (WASPAS)" method, decision-makers can evaluate options across multiple criteria. This involves assigning weights to each criterion, scoring each option, and calculating the overall results to determine the best choice. According to the results, Destination A ranks highest, while Destination E ranks lowest.

An integrated three-way decision methodology for sustainability of wastewater circularity in thermal power plants

The presence of multiple criteria for evaluating wastewater reuse applications indicates the potential usage of Multi-Criteria Decision-Making (MCDM) methods for this purpose. However, there is currently a scarcity of studies in the domain literature that utilize MCDM approaches in this application topic. This paper therefore advances the domain literature in two distinctive ways. Firstly, it analyzes and advances the reuse agenda of wastewater from thermal power plants, recognized as large-scale users of water, thus promoting greater water circularity. Secondly, it provides a methodological advance by integrating the notion of Three-Way Decision (3WD) into the computational structure of MCDM methods by introducing a middle reference point. Such an initiative results in a novel 3WD extension of the Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) method. Additionally, this work provides a proof that the MARCOS method utilizes a compromise solution in identifying priority alternatives, along with the integration of a Weighted Aggregated Sum Product ASsessment (WASPAS) metric. An initial hypothetical example illustrates how the proposed approach augments the canonical MARCOS method, particularly in promoting the “thinking in threes” as a more natural information processing approach and the high degree of distinguishability of priorities between decision alternatives. An actual case study in a thermal power plant then demonstrates the contributions of this work. With the best-worst method used to determine the priorities of the decision attributes, the findings reveal that wastewater reuse applications achieving reduced costs for needed infrastructures, operational simplicity, technological compatibility, consumer safety and household savings are preferred by stakeholders. The 3WD-MARCOS approach identifies industrial and commercial use, municipal use, environmental restoration, and household use as the high-priority alternatives, with cooking and drinking as least preferred. These insights guide stakeholders in their design of initiatives that allocate resources for greater wastewater reuse. A comparative analysis yields high consistency of these findings with similar MCDM methods. In addition, the efficacy of the novel 3WD-MARCOS method highlights its potential in handling MCDM problems, including those promoting water circularity.