Fuzzy TOPSIS Research Articles

A novel Fuzzy TOPSIS based hybrid jarratt butterfly optimization for optimal routing and cluster head selection in WSN

A novel Fuzzy TOPSIS based hybrid jarratt butterfly optimization for optimal routing and cluster head selection in WSN

Performance assessment and comparison of online food delivery service providers based upon the aggregated perspectives of restaurant operators

Online food delivery businesses have grown rapidly during the past few years. To attract customers, food delivery service providers are forming partnerships with as many restaurants as possible. For restaurant entrepreneurs, the selection of the best service provider is a critical decision that influences their sales. However, many qualitative criteria make this problem difficult. Although rating scales can convert subjective judgments into quantitative analysis, linguistic scales may make a comparison of alternatives’ performances vague and unstandardised, especially for group decision making. The prioritisation of the criteria importance is also questionable, and reaching a consensus among decision makers might be difficult. To address such complications, this study proposes the use of fuzzy logic in determining the importance weights of the criteria in the direct rating approach, based on the perspectives of 60 restaurant operators in Thailand. The fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) is then used to rank alternatives, as demonstrated by a case of three food delivery providers in Thailand. Fuzzy simple additive weighting (fuzzy SAW), two rank-based weighting methods (rank sum and rank-order centroid), and two objective weighting methods (entropy and mean) are used to compare results. The results show that user-friendly apps, tracking systems, payment options, marketing campaigns, and service areas are among the important criteria that delivery service providers should address and improve in order to attract more restaurants and customers. Guidelines for restaurant operators to choose the appropriate weighting methodology and to rationally assess and compare the service providers’ performances are provided.

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.

Prioritization and taxonomy of factors related to environmental tax reform (ETR) using fuzzy AHP approach

PurposeEnvironmental taxes have been in place for many years to reduce environmental damage and pay more attention to the environment. However, some of the adverse socio-economic impacts that may result from such taxes and the many challenges facing developing countries have necessitated policy reform. Therefore, identifying and prioritizing the factors related to environmental tax reform (ETR) is necessary to help governments and environmental protection agencies (EPAs) focus on this prioritizing to develop and improve this process. Awareness of the benefits of ETR encourages governments to use this policy to reduce adverse environmental impacts and contribute to economic growth.Design/methodology/approachThe primary purpose of this work is to prioritize and taxonomy the factors related to ETR using the Fuzzy Analytic Hierarchy Process (FAHP) approach. In the first stage, 25 factors were extracted from the available literature. These factors were divided into five categories for more accessible review. In the second stage, the FAHP as a Multiple-Criteria Decision-Making (MCDM) Technique was used to prioritize and develop the taxonomy of identified factors and the categories of these factors.FindingsThe results show that reducing carbon emissions (DF4) is the essential prioritization factor that governments and environmental organizations can achieve if the ETR is implemented. Following that, reducing greenhouse gas emissions (DF1), double benefit (EcF7) and increase sustainability reports (EnF4) can be achieved by implementing ETR.Research limitations/implicationsThis study is geographically limited to Iran. In terms of the study population, this study is limited to 25 academic, tax and public policy experts. Moreover, in this study, FAHP is the only approach used. For further research, the results of this study can be compared with that of other multi-criteria techniques like FAHP, fuzzy TOPSIS or BWM.Practical implicationsRatings of factors related to ETR can guide and help governments identify important factors that affect environmental tax reform, which can, in addition to controlling ecological pollution will, increase the economic benefits of governments.Originality/valueThis study is the first to identify factors related to environmental tax reform and to develop an MCDM technique for prioritizing these factors and finding important ones.

Toward Effective Uncertainty Management in Decision-Making Models Based on Type-2 Fuzzy TOPSIS

Over the past century, there has been a dramatic increasing interest in the multi-criteria group decision-making (MCGDM) technique, with a considerable amount of studies published regarding it. One of the well-known approaches in the MCGDM paradigm is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The integration of the TOPSIS method with fuzzy set theory has proven to be successful in various applications. Recently, a wide array of publications has proposed implementing a type-2 fuzzy set with TOPSIS. However, the additional degree of uncertainty represented by type 2 has largely been ignored, especially in a few specific mathematical operations in the model. We propose constructing interval type-2 fuzzy membership functions (IT2 MFs) using interval-based data gathered from a survey, where this is used to generate a new scale to represent ratings for each alternative. This procedure utilized all information gathered from decision makers. In addition, we present a complete algorithm for TOPSIS based on IT2 fuzzy sets (IT2 FSs) which preserve the interval-based form output. The output in the form of intervals offers decision makers (DMs) with more detailed information, enabling them to make more nuanced decisions. This can include cautious decisions when intervals are wider and overlapping. Although understanding the exact meaning of these intervals and their widths in a decision-making context is challenging, this paper introduces a systematic method for connecting input uncertainty to output uncertainty in the TOPSIS technique. This approach establishes a solid foundation for future research. Thus far, no other researchers have suggested a data-driven method that combines TOPSIS with fuzzification and provides intervals as the final output.

Application of fuzzy group decision-making selecting green supplier: a case study of the manufacture of natural laurel soap

The selection of suppliers alone is one of the most important competitive challenges facing organizations today. With today's increasing awareness and facing many significant environmental pressures, the process of selecting the right suppliers for green supply chain management is even more difficult for decision-makers. The process of developing and implementing decision-making tools seek to face these challenges is rapidly evolving, especially in a fuzzy environment whose data are incomplete. The purpose of this article is to investigate prospective green chain suppliers for a laurel soap producing company based on a framework using MCDA fuzzy technologies such as Fuzzy GRA, Fuzzy TOPSIS, and Fuzzy VIKOR. During this paper, a discussion of fuzzy set was discussed with Fuzzy MCDM. Within a realistic case study, where a comparison was made between the tools, and it was noted that the results were consistent between the two tools Fuzzy TOPSIS and Fuzzy GRA, and the arrival of similar results and a slight difference with results was observed in Fuzzy VIKOR interpreted. The most detailed analyses were conducted on distance measurements, linguistic variables, assembly functions, and confusion processing. This study introduces the Fuzzy MCDM method to help researchers choose a more effective approach for green supplier selection and the conclusions and other study directions are offered toward the conclusion of the paper.

FUZZY-TOPSIS method for defining optimal parameters and finding suitable sites for PV power plants

This study aims to assess and locate the potential for solar power plants (SPP) by utilizing TOPSIS decision analysis and based Fuzzy-Boolean logic based on GIS in Tehran province, Iran. GIS was used as a robust tool for data processing to gather practical and necessary information for effective resources and facilities. Through the multicriteria decision-making method (MCDM), alternative sites were identified and prioritized. The fuzzy logic method was employed to evaluate regions and generate thematic maps, revealing that approximately 95% (14,350 km2) of the region's area was unsuitable for constructing a power plant, while 5% (741 km2) was suitable. From the suitable areas, nine locations were selected for photovoltaic plant construction, totaling 22 km2, occupying 0.15% of the province's total area. Fuzzy TOPSIS was then used to prioritize the alternatives, resulting in the selection of Ghiyeh Naserieh in the southern part of the province as the preferred location for the power generation unit.

Aircraft Selection Decision Support Model for Fleet Planning of the Low Cost Airlines

In this study, a decision support model was created for the aircraft type selection in the fleet planning decision of a low-cost airline and 21 sub criteria were determined for the model in five main groups as technical, economic, environmental, political and other criteria. In this decision support model, the Fuzzy TOPSIS and Fuzzy MOORA Multi Criteria Decision methods were applied, and 17 different narrow body aircraft types produced by Airbus, Boeing, Embraer, and Airbus/Bombardier aircraft manufacturers were evaluated. In the evaluation, it was found that Airbus A321NEO was the most preferable aircraft for the low-cost airline business model among the aircraft types.

A combined fuzzy AHP with fuzzy TOPSIS to locate industrial supporting bonded logistics centers

Raw material availability is critical for the sustainability of industrial activity. A bonded logistics centre is required as a multipurpose warehouse for the storage of raw commodities, particularly those imported from other countries. The operationalization of bonded logistics centers in terms of supplying raw materials effectively and efficiently is largely location dependent. Proper facility placement is critical for resolving the storage issue and boosting the efficiency of the transportation system. The purpose of this article is to suggest a technique for locating a bonded logistics centre. In an unpredictable context, decision making requires a range of criteria generated from knowledge and stakeholder experience. As a result, this work proposes the combination of the fuzzy analytic hierarchy process (FAHP) with the fuzzy technique for ordering preferences by similarity to ideal solution (FTOPSIS). By disclosing linguistic characteristics, fuzzy numbers contribute to the resolution of ambiguity and imprecision. Obtaining the weighted value of the criteria and sub-criteria using fuzzy AHP. Using fuzzy TOPSIS, determining alternate preferences based on weighting factors. Its use lies in being able to distinguish between criteria that provide advantages and those that generate expenses. The findings indicate that the selected option is the one that is most closely related to the positive ideal.

Pythagorean Fuzzy TOPSIS Method for Green Supplier Selection in the Food Industry

Pythagorean Fuzzy TOPSIS Method for Green Supplier Selection in the Food Industry

Identifying and prioritizing barriers and challenges of Social Innovation implementation in the Public Sector

Social innovation (SI) is one of the latest approaches for empowering the public sector (PS). Because of the bureaucratic nature of the PS, implementation of social innovations in PS faces many challenges. This study is trying to identify and prioritize these barriers and challenges focusing on the judicial sector. This study has used a mixed-method. In the qualitative stage, by reviewing the literature and applying the focus group interview method with 12 experts, 40 barriers and challenges were organized into seven categories. In the quantitative step, 18 experts that were identified based on the purposive sampling method have answered the questionnaire and the challenges were prioritized using a fuzzy TOPSIS method. The results showed that the lack of a proper regulatory system for social innovators is the main challenge the SI faces in the judicial system. Finally, structural, functional, and behavioral recommendations were provided to remove these barriers.

A systematic decision-making framework for tackling quantum software engineering challenges

Quantum computing systems harness the power of quantum mechanics to execute computationally demanding tasks more effectively than their classical counterparts. This has led to the emergence of Quantum Software Engineering (QSE), which focuses on unlocking the full potential of quantum computing systems. As QSE gains prominence, it seeks to address the evolving challenges of quantum software development by offering comprehensive concepts, principles, and guidelines. This paper aims to identify, prioritize, and develop a systematic decision-making framework of the challenging factors associated with QSE process execution. We conducted a literature survey to identify the challenging factors associated with QSE process and mapped them into 7 core categories. Additionally, we used a questionnaire survey to collect insights from practitioners regarding these challenges. To examine the relationships between core categories of challenging factors, we applied Interpretive Structure Modeling (ISM). Lastly, we applied fuzzy TOPSIS to rank the identified challenging factors concerning to their criticality for QSE process. We have identified 22 challenging factors of QSE process and mapped them to 7 core categories. The ISM results indicate that the ‘resources’ category has the most decisive influence on the other six core categories of the identified challenging factors. Moreover, the fuzzy TOPSIS indicates that ‘complex programming’, ‘limited software libraries’, ‘maintenance complexity’, ‘lack of training and workshops’, and ‘data encoding issues’ are the highest priority challenging factor for QSE process execution. Organizations using QSE could consider the identified challenging factors and their prioritization to improve their QSE process.

Sustainable Performance Assessment towards Sustainable Consumption and Production: Evidence from the Indian Dairy Industry

The current global economic status quo is widely seen as unsustainable in the food sector. The field of sustainability science is still rather fragmented, covering a wide range of techniques and issues, despite the large number of publications in this area. Due to population growth, the food supply chain (FSC) and farmers have to produce more food. The UN estimates that one-third of edible food is wasted, producing greenhouse gases. A balance must be struck between company operations and social, environmental, and economic activities for sustainable development of the FSC. To assist FSC organizations in managing sustainable advancement, this study created a methodology for the assessment of sustainable performance. We provide a sustainable assessment system using a fuzzy analytic hierarchy process, fuzzy VIKOR, and fuzzy TOPSIS. Our research framework evaluated the sustainability of three cooperative-society-run Indian dairy firms. Our study gives environmental criteria the highest weight (0.33) and social criteria the lowest (0.16), with economic reasons (0.306) and business operations (0.204) falling in the middle. Supply chain costs, on average, are given the highest weight, and capacity utilization, the lowest weight. Three dairy industries are ranked (DPI3, DPI1, and DPI2) based on sustainable performance. By modifying the maximum set utility value and validating VIKOR results with TOPSIS, we have checked the robustness of this performance assessment tool. This research aids dairy businesses in achieving several Sustainable Development Goals, including sustainable production and consumption, through the regular assessment of their sustainable performance.

Hybrid multi-criteria decision-making technique for the selection of best cryptographic multivalued Boolean function

Robustness of modern information confidentiality algorithm depends on its individual components. Modern block ciphers highly depend on two components namely confusion and diffusion. These two main characteristics in any modern cipher are achieved by substitution and permutation boxes. In this article, a decision-making algorithm is utilized for the selection of optimum substitution box (S-box), which plays a significant role in the field of information confidentiality. For this purpose, an interval-based Pythagorean fuzzy technique for order of preference by similarity to the ideal solution (IVPF–TOPSIS) method is introduced to get the desired nonlinear confusion component of block cipher namely S-box. In this manner, we performed cryptographic analyses of standard S-boxes namely nonlinearity (NL), strict avalanche criterion (SAC), bit-independent criterion (BIC), absolute indicator (ABI), the sum of square and absolute indicator (SSAI), algebraic degree (AD), algebraic immunity (AI), transparency order (TO), composite algebraic immunity (CAI), robustness (RB), signal to noise ratio (SNR), confusion coefficient of variance (CCV). With these cryptographic characteristics, we have used interval-valued based Pythagorean fuzzy TOPSIS multi-criteria decision-making technique to classify standard S-boxes suitable for construction of modern block ciphers.

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.

A weighted centroids approach based trapezoidal interval type-2 fuzzy TOPSIS method for evaluating agricultural risk management tools

A weighted centroids approach based trapezoidal interval type-2 fuzzy TOPSIS method for evaluating agricultural risk management tools

A comprehensive approach to selecting mine transportation system using AHP and FUZZY-TOPSIS

Mine transportation approximately accounts for more than half of operating costs. Therefore selection of the appropriate mine transportation system by considering the effective criteria has become an important issue in mining engineering. A hybrid decision support system based on Analytical Hierarchy Process (AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) was proposed to assess criteria and alternatives for balancing haulage distance, continuity, flexibility and reliability, which could provide the suitable balance between different goals, such as costs and safety. An application of this approach is carried out through the Sungun copper mine as case study. For this purpose, the production capacity, medium and short-term production plan, conditions of mining benches and ramps and future development plans collected from chosen mine located at the East Azerbaijan Province, Iran. This research has been studied comprehensively in terms of technical, economic, environmental, society, site information, geological and geo-mechanically criteria. More than 170 criteria were identified and classified under six main categories. To select the mine transportation system, the importance of each criteria is first measured relative to each other, then the importance of each option is evaluated for each criteria and were filtered to 55 items. The proposed model is based on the combination of the AHP and fuzzy TOPSIS. The hybrid model has advantages such as the possibility of using paired comparison and considering uncertainty. Finally, the in-pit crushing and conveying is selected as the best alternative, the truck-front shovel and truck-backhoe system are in the next priorities, respectively 45.2, 28.4 and 26.4%. In summary, from the results of the research, it can be mentioned to present the effective criteria in the selection of the transport system of open pit mines, to calculate their weight, to provide a framework for the selection of the transport system of open pit mines by considering the uncertainties.

TOPSISort-L: An extended likelihood-based interval-valued intuitionistic fuzzy TOPSIS-sort method and its application to multi-criteria group decision-making

In real-world multi-criteria group decision making challenges, decision makers typically provide imprecise or ambiguous information due to a lack of knowledge, time constraints, or restrictions regarding information disclosure. In order to deal with this sort of imprecision caused by experts' subjective evaluation, fuzzy sets have been suggested. When compared to traditional fuzzy sets, interval-valued intuitionistic fuzzy sets, also known as IVIFSs, are superior when it comes to dealing with subjective ambiguity and incomplete information. For these reasons, this work provides a novel extension for the TOPSIS technique by employing likelihoods of IVIFSs, and introduces a methodology named as TOPSISort-L that is capable of classifying alternatives under a variety of circumstances. We begin by developing the conventional fuzzy TOPSIS technique by using a newly proposed decision matrix, a novel selection mechanism for ideal solutions, and a generalized likelihood-based closeness metric for the purpose of alternative ranking. After that, the TOPSISort-L algorithms are presented to obtain an accurate classification for the alternatives when there are information about the characteristic profiles, and also obtain an approximate classification when information about the characteristic profiles is missing. Eventually, by contrasting the approach with various different methodologies now in use, we exhibit the validity and adaptability of the method.

HSE hazard ranking of chemicals related to Petroleum Drilling Laboratory of University using Fuzzy TOPSIS

HSE hazard ranking of chemicals related to Petroleum Drilling Laboratory of University using Fuzzy TOPSIS

Integration of ABC Analysis with Fuzzy DEMATEL and Fuzzy TOPSIS in Supplier Selection and Ranking Problems

While performing Always Better Control (ABC) analysis in an automobile industry, A category items are given higher priority, neglecting B and C category items which comprise 80% of the total inventory. Little attention to tail spend account poses problems in managing suppliers, unscheduled deliveries, and environmental issues. To address this gap a Multi-criteria decision making approach is proposed for supplier selection in each inventory class by integrating ABC Analysis with Fuzzy Decision-making trial and evaluation laboratory and Fuzzy Technique for Order Preference by Similarity to Ideal Solution. The best suppliers are selected based on criteria weights and criteria interrelationships for each A, B, and C inventory items. The study shows that managers have to focus on key criteria rather than a whole set of criteria for A, B, and C inventory suppliers thus saving costs and effort. The results show that delivery and environmentally friendly products as common and important criteria for supplier selection in each inventory items. The research results will help the decision-makers and policymakers in solving the supplier selection problems in the automobile sector and other similar sectors.