Fuzzy TOPSIS Approach Research Articles

A Consensus Framework for Evaluating Dispute Resolution Alternatives in International Law Using an Interval-Valued Type-2 Fuzzy TOPSIS Approach

This research is motivated by the arbitrary nature of decision-making environments and the dynamic changes in decision patterns, particularly in international dispute resolution. These challenges introduce uncertainties that could be effectively managed by fuzzy logic, which provides a robust framework for evaluating alternatives under multiple criteria. In this study, an Interval-Valued Type-2 Fuzzy TOPSIS approach is proposed to assess various dispute resolution methods, including negotiation, good offices, mediation, international inquiry, conciliation, international organization, arbitration, and international jurisdiction. Common criteria are determined by examining academic literature and by interviewing relevant experts.—cost-efficiency, duration, impartiality, binding nature, and generalizability are considered essential in determining the best resolution method. The proposed method allows for a nuanced evaluation by incorporating both primary and secondary levels of uncertainty, enabling decision-makers to determine the best alternative solution more reliably. This method’s application extends not only to the international law field but also to industrial engineering, where complex, uncertain decision environments require similarly sophisticated multicriteria decision-making tools. By systematically analyzing these resolution methods, this study aims to provide a structured, quantifiable approach that enhances the decision-making process for both international legal practitioners and engineers working with uncertain and dynamic systems. The results of this study ultimately contribute to improved decision-making outcomes and greater efficiency in multidisciplinary problem solving. The assessments of experts in international law, international relations, and political science in their respective fields of expertise have been gathered to form a consensus. This study contributes to the literature as it is the pioneering application of fuzzy multicriteria decision-making techniques in the field of international law. The results of this study imply that the best option from the different decision-maker evaluations is international jurisdiction. Consequently, the utilization of multicriteria decision-making tools can result in more informed and effective decisions in complex and uncertain situations, which is advantageous to both legal practitioners and engineers. Additionally, incorporating different disciplines can help streamline the decision-making process and improve overall efficiency in solving multidisciplinary problems.

Optimal Management of Energy Storage Systems in Hospitals with Quantum Spherical Fuzzy Decision-Making Modelling

The purpose of this study is to identify prioritized strategies to increase the effectiveness of energy storage investments in hospitals. For this purpose, 5 literature-based criteria affecting energy storage investments in hospitals are identified. These criteria are weighted by the quantum spherical fuzzy DEMATEL method. On the other side, 4 different renewable energy alternatives are identified. The performance of these alternatives are ranked with quantum spherical fuzzy TOPSIS approach. It is determined that storage capacity is the most critical factor to increase the effectiveness of the energy storage systems in the hospital. Similarly, technological infrastructure is another key issue for the development of this process. However, it is also seen that security issues, legal effectiveness and financial situations have the lower weights. In addition to them, the ranking results demonstrate that wind energy is the most appropriate renewable energy type with respect to the energy storage performance of the hospitals. Geothermal energy can also be considered for this situation. On the other hand, solar and hydropower energy types have lower performance in this framework.

A study of appropriate wave energy technology for sustainable development in Australia

The deployment and development of wave energy systems to increase energy sector efficiency is essential for governments. To develop and maximize the exploitation of wave energy sources, applying appropriate technologies is extremely important. The design of decision-making tools to identify the best technology for developing energy resources optimally is one of the primary decision-making issues in the energy sector. In this article, we have proposed a Multi-Criteria Decision Making (MCDM) model to select suitable technologies among eleven wave energy harvesting technologies: OPT PowerBuoy, AquaBuoy, Archimedes Wave Swing, Salter’s Duck, Aquamarine PowerOyster, Bio Wave, SEAREV, Weptos, Mighty Whale, Wave dragon. To handle conflicting objectives during evaluation, the Fuzzy AHP method is used to calculate the weight of the criteria. Then, wave energy harvesting technology is ranked using the Fuzzy TOPSIS approach. An actual case study from Australia was examined in order to show the viability of the suggested decision-making methodology. This study applies a valuable reference to the issue of wave technology selection; Therefore, managers involved in wave energy can use the problem-solving approach in this study to identify the most suitable wave energy technology based on their criteria. Research results show that the most suitable technologies for optimal development of wave energy sources in Australia are WET-05 and WET-03 with coefficients of 0.852 and 0.806, respectively. Meanwhile, two technologies considered unsuitable for developing wave energy sources in this study are WET-06 and WET-11 with scores of 0.375 and 0.381, respectively. In this study, the combined application of the two FAHP-FTOPSIS methods is considered more appropriate because of its theoretical ease of understanding as well as the simplicity of application and robustness of the results.

Evaluation of Spatial Variations in Surface Water Quality of Mahanadi River Basin by Geospatial-FUCOM based Prediction Utilising Fuzzy-TOPSIS Approach

This study highlights an evaluation of surface water quality for drinking purposes in Mahanadi River Basin, Odisha using Full Consistency Method (FUCOM) based WQI (FU-WQI), with reliability-based MCDMs (Multiple-criteria decision making) such as Fuzzy-TOPSIS (F-TOP). Water samples from 19 locations were taken during the period 2018-2023 to test 20 physicochemical parameters. Further, the FU-WQI revealed that 36.84% (n=7 sites) and 5.26% (n=1) of samples belong to poor/unsuitable water quality while 47.37% of sites come under the zone of excellent water (n=9 locations). However, 10.53% of samples indicated a medium water quality. The analysis primarily revealed that at 8 samples, deterioration of domestic water, illegally dumped municipal solid waste, and agricultural runoff were the leading sources causing adulteration of the river’s water quality. As a result, a renowned MCDM model, such as F-TOP, was implemented to resolve conflicts regarding the WQI index. Hence, this innovative technique showed that SP-(9) was the most polluted in comparison with other locations, followed by SP-(8), (19), and (2). This was also accompanied by high values of nine crucial parameters, which were also higher than their desirable concentration and highest among all the locations. Following this, the analytic findings also suggest the same from the FU-WQI values 423, 198, 182 and 184 at these locations. However, it was pertinent that the pollution level at these stations was associated more with increasing and diverse anthropogenic activities. So, it is found that river water is convenient for household usage and, after disinfection, fit for human consumption.

Analytic Hierarchy Process to Choose the Best Sector in the Software Industry for a New Software Engineer

Objectives: To determine the best area in the software industry for a fresh engineering graduate in India. Methods: Examined the current situation of the software industry today and the datasets that were gathered and included in accordance with that. Here, five alternatives (Research and Development, Mobile solutions, Cloud computing, Big data analytics, and Government and Defence) and seven parameters (Communication, Teamwork, Coding and technical literacy, Programming languages, Problem-solving skills, Research skills, and Multitasking skills) are taken into consideration. Fuzzy AHP and fuzzy TOPSIS methods were used, and the outcomes were compared to the AHP method. Findings: Fuzzy AHP and fuzzy TOPSIS methods have been used to produce the normalized weight vector for each alternative relative to the criterion. Additionally, a normalized weight vector has been calculated and compared to every criterion and criteria alternative. Final rankings for each alternative have been determined in relation to all of these. Novelty: The novelty of the present study is to identify the best sector of the software industry in India for a recent engineering graduate based on providing a ranking of alternatives using fuzzy TOPSIS and fuzzy AHP methodologies. While other strategies may be used to do similar works, the techniques listed above may not be used. Fuzzy AHP and fuzzy TOPSIS approaches can provide more optimal solutions, which is an innovative aspect of this study. Keywords: Analytical Hierarchy Process (AHP), Comparative analysis, Fuzzy AHP method, Fuzzy TOPSIS method, Software industry

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.

Efficient fuzzy multi-criteria decision-making for optimal college location selection: A comparative study of min–max fuzzy TOPSIS approach

Ranking fuzzy values is often essential in fuzzy multi-criteria decision-making (FMCDM) systems since it is established on the comparison of hazy data pairs, even though the comparison needs temporal complexity. Then to provide a fuzzy MCDM approach under min–max operations for avoiding the fuzzy comparison. By using fuzzy TOPSIS’s min and max operations, the suggested method produces two positive and negative ideal solutions of each alternative. Here, before discussing the effectiveness of the matrices between the alternatives, first to analyze the weighted strength and weakness indices from both positive and negative indices. The results of the method have been described using a straightforward case study of a proper location for creating a college. The best location can be identified using this method based on various criteria. The outcomes are also compared with the suggested method for its effectiveness. Additionally, this problem analyzes the fuzzy TOPSIS approach in an interval-valued number for greater efficiency.

An extension of fuzzy TOPSIS approach using integral values for banking performance evaluation

Banks play a crucial role as financial intermediaries in advancing economies. Increasing market share is a top priority for all banks in today's fiercely competitive market. To achieve this, banks are expected to enhance their efficiency, which boosts their competitive capacity and helps decision-makers identify areas for development. This paper introduces an extended fuzzy TOPSIS approach that incorporates integral values to assess banking performance. Our method includes the averaging and normalization of decision-makers assigned ratings and weights, ensuring a standardized scale for comparison. Subsequently, we create membership functions for the ultimate fuzzy evaluation values of alternatives using interval arithmetic for fuzzy numbers. We employ a novel fuzzy number ranking method based on integral values to streamline the aggregation of fuzzy numbers to defuzzify the weighted ratings. Ultimately, we introduce a closeness coefficient for determining the ranking order of alternatives by computing their distances to both the positive and negative ideal solutions. To illustrate the effectiveness and applicability of our proposed method, we present an application example.

Appraisal of pollution and health risks associated with coal mine contaminated soil using multimodal statistical and Fuzzy-TOPSIS approaches

Appraisal of pollution and health risks associated with coal mine contaminated soil using multimodal statistical and Fuzzy-TOPSIS approaches

Neuro quantum-inspired decision-making for investor perception in green and conventional bond investments

The purpose of this study is to make a comprehensive analysis of investor perceptions in the context of green and conventional bond investments. For this purpose, a new model is presented by considering two steps. First, a criteria set is generated by considering balanced scorecard perspectives that are finance, customer, organizational effectiveness and learning and growth. After that, the neuro Quantum fuzzy M-SWARA method is considered to weight these criteria. Secondly, seven critical determinants for bond investments are identified that are coupon rates, volume, maturity, riskiness, liquidity, volatility, and tax considerations. Neuro Quantum fuzzy TOPSIS approach is employed to rank these factors. The main contribution of the study is that by combining the balanced scorecard framework and quantum-inspired decision-making techniques, this paper offers a novel and sophisticated decision-making model to understanding investor behavior. Similarly, in the proposed model, a new methodology is generated by the name of M-SWARA. In this framework, some enhancements are adopted to the SWARA technique. The weighting results indicate that meeting customer expectations is the most critical factor that affects the investor perception to make investments to the bonds. Moreover, according to the ranking results, it is concluded that coupon rates are the most important item for both conventional and green bond investors. On the other hand, with respect to the conventional bond investor, tax is the second most essential factor. However, regarding the green bond investors, volatility plays a critical role. AcknowledgmentThis research has been/was/is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (№ AP 19679105 “Transformation of ESG financial instruments in the context of the development of the green economy of the Republic of Kazakhstan”).

A Literature Review on Fuzzy-TOPSIS Approach in Material Selection

A Literature Review on Fuzzy-TOPSIS Approach in Material Selection

Fuzzy multi-criteria decision-making framework for controlling methane explosions in coal mines

The structure of underground coal mines is vulnerable to many mishaps because of the challenging conditions of production and the unique features of the earth. These incidents could cause significant financial and production losses for the mines in addition to worker injury, disability, or death. In coal mines, methane explosions are a frequent threat. Establishing a safe work environment requires managing these problems with an accident control method. The current study used the fuzzy TOPSIS and fuzzy AHP techniques for this aim. The framework was used to tackle the four-alternative problem of underground coal mine explosion control method selection. To identify potential risks of a methane explosion, a data gathering survey was conducted as part of the suggested hybrid methodology. The fuzzy AHP was used to compute the fuzzy weights of the hazards. “Improper ventilation system” is ranked highest out of the 34 sub-risk factors. The fuzzy TOPSIS was then utilized to rank the explosion control methods using the weights. To assess the viability of the study’s conclusions, a sensitivity analysis was carried out. The findings indicate that “improving safety technology” and “financial investments” are the best ways to reduce such events. The results additionally indicate that the fuzzy TOPSIS approach in combination with the fuzzy AHP provides a helpful framework for dynamically assessing mine methane explosion accidents.

Greening Human Resource Management in Manufacturing Organizations: A Fuzzy TOPSIS Approach to Prioritizing Sustainable Practices in Western Odisha

Greening Human Resource Management in Manufacturing Organizations: A Fuzzy TOPSIS Approach to Prioritizing Sustainable Practices in Western Odisha

Correction to: An Interval‑Valued Trapezoidal Intuitionistic Fuzzy TOPSIS Approach for Decision‑Making Problems

Correction to: An Interval‑Valued Trapezoidal Intuitionistic Fuzzy TOPSIS Approach for Decision‑Making Problems

Multi‐objective decision trees with fuzzy TOPSIS: Application to refugee resettlement planning

AbstractThis study combines the use of multi‐objective decision trees (MODT) and a fuzzy TOPSIS approach to cope with sequential decision‐making under uncertainty with multiple conflicting objectives. To this aim, the MODT generates a Pareto‐optimal frontier of solutions for competing objectives, while fuzzy TOPSIS helps assess the noninferior solutions and assign weights to the objectives by considering possible uncertainties in outcomes as well as potential linguistic expression. The proposed approach is illustrated with a temporal decision problem concerning climate‐driven refugee resettlement, taking into consideration the challenges of global warming and system interdependencies in an uncertain context. The fuzzy TOPSIS approach was illustrated using two different procedures, and the procedure based on vector normalisation graphically depicts the fuzzy triangular representation of the final ranking.

How COVID-19 pandemic influenced the countries? A value at risk based fuzzy TOPSIS approach using IF–THEN rules

How COVID-19 pandemic influenced the countries? A value at risk based fuzzy TOPSIS approach using IF–THEN rules

A stable matching method for technology trading with intuitionistic fuzzy multi-attribute information

Technology trading matching facilitates quicker solution-finding for technology demanders and expedites the transformation of scientific and technological achievements. Yet, unstable matchings often lead traders to renounce existing contracts, sidestep trading intermediaries, and resort to private transactions. This results in inefficient trading mechanisms and market disarray. To ensure a stable and mutually satisfactory match for both suppliers and demanders, we propose a stable two-sided matching decision-making method that incorporates intuitionistic fuzzy multi-attribute information. Initially, we introduce an intuitionistic fuzzy TOPSIS approach to compute the comprehensive satisfaction of both suppliers and demanders by aggregating intuitionistic fuzzy information across various attributes. Subsequently, we design a multi-objective optimization model that weighs both stability and satisfaction to determine the ideal technology trading pairs. We conclude with a real-world example that demonstrates the proposed method’s application, and its effectiveness is corroborated through sensitivity and comparative analyses.

A Fuzzy-TOPSIS-Based Approach to Assessing Sustainability in Software Engineering: An Industry 5.0 Perspective

New possibilities and challenges have evolved in the setting of the software engineering sector’s rapid transition to Industry 5.0, wherein sustainability takes centre stage. Appropriate evaluation approaches are required for analysing the long-term viability of software engineering practices within this paradigm. This study proposes an innovative approach to evaluating sustainability in software engineering within Industry 5.0 by utilising the fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS) methodology. The fuzzy TOPSIS approach is effective at accounting for the inherent uncertainties as well as imprecisions related to sustainability assessments, allowing for informed decision-making. This approach helps in the recognition of the most sustainable software engineering practices in Industry 5.0 by taking into account a defined set of sustainability parameters. We rigorously analyse the current literature and expert views to provide an extensive set of relevant sustainability standards for the area of software engineering. Following that, we develop an evaluation methodology based on fuzzy TOPSIS that can handle the subjectivity as well as fuzziness inherent in sustainability evaluations. A case study with a software development company functioning in Industry 5.0 demonstrates the utility and efficacy of our suggested framework. The case study outcomes reveal the benefits and drawbacks of various software engineering methodologies in terms of sustainability. The study’s findings provide substantial information for decision-makers in the software engineering field, assisting them in making educated decisions about sustainable. Finally, this study helps to establish environmentally and socially appropriate techniques within the context of Industry 5.0.

A Fuzzy TOPSIS-Based Approach for Comprehensive Evaluation of Bio-Medical Waste Management: Advancing Sustainability and Decision-Making

Bio-medical waste management is critical for ensuring public health and environmental sustainability. However, due to the inherent ambiguities and complexities involved with waste characteristics and disposal techniques, measuring the efficiency of bio-medical waste management systems presents major hurdles. This study provides a Fuzzy TOPSIS-based (Technique for Order Preference by Similarity to Ideal Solution) strategy for thorough bio-medical waste management assessment. The suggested method combines the benefits of fuzzy logic and TOPSIS, allowing for the incorporation of subjective judgments and ambiguity in the evaluation procedure. Initially, a thorough set of criteria is constructed based on a review of current literature and recommendations from experts, comprising Environmental Impact, Compliance with Regulations, Health and Safety, Technological Feasibility, and Cost-effectiveness. To accurately represent the inherent ambiguity and imprecision in decision-making, each criterion is evaluated using linguistic variables. Furthermore, the Fuzzy TOPSIS approach is used to rate various bio-medical waste management systems depending on how well they perform in comparison to the identified criteria. The language judgments are represented as fuzzy numbers, and the idea of closeness coefficients is used for calculating the relative distance between each alternative and the ideal answer. An investigation in a healthcare facility is performed to demonstrate the feasibility and effectiveness of the suggested strategy. To assess numerous waste management approaches, the study uses real-world data on waste management practices, expert opinions, and linguistic analyses. The study’s findings emphasize the benefits of using a Fuzzy TOPSIS-based technique to evaluate bio-medical waste management. According to the findings of this research study, recycling is the best choice because it has the potential to reduce waste, recover resources, and preserve the environment. It assists decision-makers to account for uncertainties and subjectivity, increases transparency and consistency in decision-making, and aids in choosing of the best waste management system. The proposed approach advances sustainable waste management practices in the bio-medical area and provides a helpful tool for policymakers and practitioners looking to enhance waste management systems.

An integrated fuzzy AHP and fuzzy TOPSIS approach for screening backfill materials for contaminant containment in slurry trench cutoff walls

The inclusion of backfill material is crucial for the effective containment of contaminants in a slurry trench cutoff wall. However, selecting the optimal backfill material is complex and involves multiple criteria. This study aimed to develop a new approach to assist in the selection process by rationally dealing with the subjective judgment of decision makers. The approach employed fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods. Initially, consistent judgment matrices were established based on a unique consulting questionnaire. The fuzzy AHP method used Buckley's method to calculate the fuzzy weights of pairwise comparisons. The fuzzy TOPSIS method was then employed to rank and evaluate four different backfill materials. The proposed methodology was successfully implemented at a real contaminated site in China to select the appropriate backfill material for construction of a slurry trench cutoff wall. Based on the proposed integrated methodology, fiber reinforced reactive magnesia-activated slag-soil-bentonite (FMSB) was determined as the most appropriate backfill materials for contaminant containment in slurry trench cutoff walls at the site reported in this study.