Fuzzy Technique For Order Preference By Similarity To Ideal Solution Method Research Articles

Applying fuzzy logic to balanced scorecard for the performance evaluation of government e-services

Purpose The purpose of this study is to assess the performance of United Arab Emirates (UAE) Government e-services by using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methodology, integrating insights from the balanced scorecard (BSC) framework across financial, customer, internal business and learning and growth perspectives. Design/methodology/approach Using the fuzzy TOPSIS method, this paper evaluate three e-services in the UAE against 12 criteria representing the balanced scorecard perspectives. Expert evaluation and sensitivity analysis are used to identify the most sustainable e-service alternative. Findings The study findings emphasize the importance of prioritizing customer-centric metrics, improving service reliability and efficiency, and investing in employee training to enhance e-government service performance in the UAE. Sensitivity analysis reinforces the robustness of our results and identifies key criteria influencing decision-making. Research limitations/implications The data was collected only from experts in selected UAE Government departments. This may affect the generalization of the findings. Also, only three e-services were evaluated. Future studies could include various e-services not covered in this study and use different multi-criteria decision-making methods. Practical implications Prioritizing customer satisfaction: Priority should be given to customer satisfaction as it is a critical factor in evaluating e-services because of its importance. It also highlights the importance of considering user feedback and ensuring that e-services have a high level of friendliness and responsiveness to their needs. It follows that minimizing errors and ensuring quick and efficient transactions are crucial. Emphasizing reliability and transaction efficiency: Reliable services and transaction efficiency are also essential criteria for evaluating e-government services. This suggests that e-government services should be designed to minimize errors and ensure that transactions are completed quickly and efficiently. Managing IT costs: To deliver e-government services affordably, effective IT cost management is crucial. This emphasizes how crucial it is to effectively manage IT costs to guarantee the efficient delivery of e-government services. Social implications From a customer perspective, adopting BSC can create a favorable customer attitude, encourage long-term customer support, and increase customer satisfaction and loyalty. These factors have significant social implications for UAE and expatriate individuals who are using such e-government services. Originality/value This study contributes to the literature by showcasing the applicability of the fuzzy TOPSIS methodology in evaluating UAE e-government service performance. By examining multiple perspectives of the BSC, this paper provide valuable insights into enhancing the efficiency and effectiveness of e-services in the UAE Government sector.

Application of Multi-Criteria Group Decision-Making Method in Interior Decoration Service

<p>值此消費者導向時代，室內設計公司應秉持以客為尊，針對客戶住宅之條件做出最適合之裝修建議，為客戶提供最完整，最優質的室內裝修服務，從而為公司贏得比其他公司更好的聲譽。五項與選擇天花板、壁面及地坪裝修有關之評估準則，依次藉由專家訪談、初步問卷及模糊德菲法(fuzzy Delphi method, FDM)取得。本研究以3個業主住宅之天花板、壁面及地坪之12個裝修項目做為研究對象，採用層級分析法(analytic hierarchy process, AHP)結合偏好順序評價法(technique for order preference by similarity to ideal solution, TOPSIS)及模糊偏好順序評價法(fuzzy TOPSIS)兩種不同分析方法，對每個裝修項目中之各替代方案進行擇優排名。12個裝修項目中，對於不同業主採用AHP結合TOPSIS及fuzzy TOPSIS兩種不同方法計算之結果顯示，共有客餐廳天花板、臥房天花板、客餐廳壁面及臥房地坪等四個裝修項目所得各替代方案之排名順序皆相同。對於廚房天花板及浴室壁面之裝修，同一業主採用AHP結合TOPSIS 及fuzzy TOPSIS兩種不同方法所得各替代方案之排名順序皆相同。兩種不同分析方法對於家庭成員僅有二人之業主3所得排名結果差異不大。本研究認為家庭成員愈多之大家庭在替代方案之排名順序應該以更具有參考價值之fuzzy TOPSIS所得之結果為準。</p> <p> </p><p>In this consumer-oriented era, interior design companies should adhere to the principle of customer-oriented, make the most suitable suggestions for the conditions of customers’ houses decoration, and provide customers with the most complete and high-quality interior decoration services, so as to win more good reputation than other companies. Five evaluation criteria related to the selection of ceiling, wall and floor decoration were obtained through expert interviews, preliminary questionnaires and fuzzy Delphi method in turn. This study takes 12 decoration projects of ceilings, walls and floors of 3 owners’ residences as the research objects, using the analytic hierarchy process (AHP) combined with the technique for order preference by similarity to ideal solution (TOPSIS) and the fuzzy TOPSIS methods to rank the alternatives in 12 decoration projects. The identical ranking order results were obtained for three owners by AHP combined with TOPSIS and fuzzy TOPSIS in the ceiling of the guest dining room, the ceiling of the bedroom, the wall of the guest dining room, and the floor of the bedroom. For the decoration of kitchen ceilings and bathroom walls, the same owner uses AHP combined with TOPSIS and fuzzy TOPSIS two different methods to obtain the ranking order of the alternatives are the same. There is little difference in the ranking results obtained by the two different analysis methods for owners 3 with only two family members. This study believes that the ranking order of alternative programs for large families with more family members should be based on the results obtained by fuzzy TOPSIS, which has more reference value.</p> <p> </p>

Streamlining apartment provider evaluation: A spherical fuzzy multi-criteria decision-making model

In the context of the thriving real estate market in developing countries like Vietnam, understanding consumer preferences and effectively addressing them through a comprehensive multi-criteria decision-making (MCDM) framework is paramount for real estate providers. This study presents a two-stage MCDM model that integrates the Delphi technique and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on Spherical Fuzzy Sets (SFSs). Initially, the SF-Delphi technique validates critical criteria influencing customers' apartment selection in Vietnam. Secondly, the SF-TOPSIS method evaluates the top ten apartment providers. To ensure robustness and validity, a comparative analysis compares the results with those from the Intuitionistic Fuzzy TOPSIS (IF-TOPSIS) and Fuzzy TOPSIS (F-TOPSIS) methods. Subsequently, five rank correlation coefficients (Spearman, Kendall, Goodman-Kruskal, Weighted rank measure of correlation, Weighted Similarity) are used to assess the relationships between various TOPSIS techniques applied to apartment suppliers in Vietnam. The correlation coefficients demonstrate strong agreement among the TOPSIS methods, with the smallest coefficient being 0.7778, surpassing the threshold of 0.7. This high level of consistency confirms the efficacy of the proposed TOPSIS approach with different Fuzzy Sets in reliably evaluating customers' preferences for apartment suppliers. Notably, the legal aspect's prominence underscores its critical role in shaping customer choices, emphasizing the significance of considering legal factors in the context of apartment supply and demand in Vietnam. Furthermore, using SFSs makes this approach particularly suited to capture consumer perceptions within the dynamic and uncertain business environment characterized by volatility, uncertainty, complexity, and ambiguity (VUCA).

CODAS extension using novel decomposed Pythagorean fuzzy sets: Strategy selection for IOT based sustainable supply chain system

Decomposed fuzzy sets (DFSs), which have been recently introduced in the field of fuzzy sets are a fuzzy set extension that deals with the membership degree and the non-membership degree of the elements in the set from a functional and dysfunctional point of view in more detail. On the other hand, Pythagorean fuzzy sets (PFSs) are another fuzzy set extension reflecting the hesitancy of decision-makers in a wider area. The main target of this study is to develop a new fuzzy set extension, decomposed Pythagorean fuzzy sets (DPFSs) in order to utilize the properties of DFSs and PFSs together. First, the basic principles and mathematical operators of the DPFSs are developed with their proofs. Then, a new fuzzy multi-criteria decision-making (MCDM) method, DPF- Combinative Distance based Assessment (CODAS) is developed to demonstrate the feasibility and effectiveness of the DPF extension. The developed method is handled in the strategy selection problem for Internet of Things (IoT)-based sustainable supply chain systems. A comprehensive sensitivity analysis is performed on both the criteria weights and the decision makers' weights to verify the stability and effectiveness of the obtained results. In addition, a comparative analysis with decomposed fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Pythagorean fuzzy CODAS and Pythagorean fuzzy TOPSIS methods is presented to show the validity, superiority and advantages of the developed method.

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.

Q-ROF Fuzzy TOPSIS and VIKOR Methods for the Selection of Sustainable Private Health Insurance Policies

As a result of the inability of people to meet their demands in the face of increasing demands, people tend to have private health insurance in addition to the general health insurance offered as a public service. Due to the increasing trend of taking out private sustainable health insurance, the number of private sustainable health insurance plans in the health insurance market has increased significantly. Therefore, people may be confronted by a wide range of private health insurance plan options. However, there is limited information about how people analyze private health insurance policies to protect their health in terms of benefit payouts as a result of illness or accident. Thus, the objective of this study is to provide a model to aid people in evaluating various plans and selecting the most appropriate one to provide the best healthcare environment. In this study, a hybrid fuzzy Multiple Criteria Decision Making (MCDM) method is suggested for the selection of health insurance plans. Because of the variety of insurance firms and the uncertainties associated with the various coverages they provide, q-level fuzzy set-based decision-making techniques have been chosen. In this study, the problem of choosing private health insurance was handled by considering a case study of evaluations of five alternative insurance companies made by expert decision makers in line with the determined criteria. After assessments by expert decision makers, policy choices were compared using the Q-Rung Orthopair Fuzzy (Q-ROF) sets Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Q-ROF VIšeKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods. This is one of the first attempts to solve private health policy selection under imprecise information by applying Q-ROF TOPSIS and Q-ROF VIKOR methods. At the end of the case study, the experimental results are evaluated by sensitivity analysis to determine the robustness and reliability of the obtained results.

Enhancing the level of confidence in the safe fire evacuation operation employing a combination of BIM and fuzzy TOPSIS method

PurposeThis research aims to provide optimization and route safety planning employing the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique.Design/methodology/approachThis research combines the use of graphical, communication tools and simulated models based on building information modeling (BIM) technology and agent-based modeling (ABM) to identify a safe evacuation route. Adopting the multi-criteria decision-making (MCDM) approach, the proposed rescue plan can reduce potential hazards along the evacuation route by selecting a safe route for evacuating residents and entering firefighters to the scene of the incident.FindingsThe results show that the use of simulated models along with MCDM methods in the selection of safe routes improves the performance of safe evacuation operations for both relief groups and residents.Practical implicationsThe introduced model can improve the performance management of different groups at the time of the incident and reduce casualties and property losses using the information received from sensors at the scene. Moreover, the proposed rescue plan prevents group and individual reactivation at the time of the incident.Originality/valueDespite many advances in the architecture, engineering and construction (AEC) industry, the number of victims of fire incidents in buildings is increasing compared to other natural disasters. Improving decision management based on effective parameters at the time of incident reduces casualties of residents and rescue workers.

An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection

PurposeSupplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).Design/methodology/approachThe proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.FindingsA fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.Originality/valueQFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

FMEA Based Fuzzy Topsis for Assessment of Quality Problems in Telescopic Platform Production

In order to increase process and product quality fast and least costly, it is very useful to focus on the process that causes the important quality problems. In this study, quality problems and related processes in a company that produces on-vehicle equipment in the automotive industry are examined. The purpose of this study is to provide a quality improvement perspective to reduce process and product defects. Fault Mode and Effects Analysis (FMEA) is applied to detect faults, determine their causes and prioritize them. Prioritization of critical quality errors is revealed using traditional FMEA and FMEA-based fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The FMEA-based fuzzy TOPSIS method has been proposed because of its ability to handle uncertainty arising from the subjective judgments of decision makers. The results are compared and the preventions are suggested to avoid from the most important process that causes the quality problem.

Fuzzy TOPSIS framework for promoting win-win project procurement negotiations.

In recent years, organizations worldwide have widely applied the project approach in business and value delivery. Negotiation is essential to the success of a project; however, it has not been explored systematically in the project context. A gap remains between knowledge and practical behavior during negotiation settlements throughout projects. Many project procurement (PP) negotiations do not work as expected. This study develops a practical framework using the scientific method to help close the gap and improve PP negotiations. The proposed framework uses the fuzzy TOPSIS (technique for order preference by similarity to ideal solution) method to integrate the PP management process (PPMP) and the three-phase negotiating model. Through this approach, notable variables and potential solutions under uncertain negotiation situations are quantitatively examined in the early stage and managed until the completion of PP. Thus, expected agreements can be obtained in a timely and efficient manner, with negotiating parties committing to implementing what has been agreed on. Such a commitment facilitates win-win outcomes. An example is presented to demonstrate how the proposed framework operates, and practical implications for managers of project-based organizations are offered. This study provides researchers and practitioners with a foundation to study refined models to enhance project negotiations with interdisciplinary integration.

Analysis of Insurance Customer Factors to Renewal Using Hybrid AHP-FTOPSIS

Human life is full of uncertainty that has enormous risks. Insurance is a one of methods that can help humans reduce those risks. Human needs for insurance causes competition among insurance companies in Indonesia to become very competitive. One factor that makes insurance companies to compete is to have its customers who make insurance renewals. Thesis discusses analysis of factors that influence insurance renewal using Analytical Hierarchy Process (AHP) method and the ranking of customer’s favorite insurance for renewal using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method. Five criteria have been determined with each criterion having subcriteria in this study. AHP method is used to calculate the weight of criteria and to determine the factors that influence customers the most to do renewal. The FTOPSIS method is used to determine the best alternative. The results of the analysis using these methods conclude was the main factor that influences the customers in conducting renewals is feature with the subcriteria of health protection needs. Meanwhile, the ranking of customer’s favorite insurance in conducting renewal is Takafulink Salam Cendikia with proximity coefficient value of 0,645, Takaful Al-Khairat with value 0,563, Takaful Dana Pendidikan with value 0,552, and Takafulink Salam with value 0,341

Online education satisfaction assessment based on cloud model and fuzzy TOPSIS

During the COVID-19, colleges organized online education on a massive scale. To make better use of online education in the post-epidemic era, this paper conducts an online education satisfaction survey with four types of colleges and 129,325 students propose a fuzzy TOPSIS (technique for order preference by similarity to ideal solution) method based on the cloud model to rank the satisfaction of different colleges. Firstly, based on the characteristics of online education during the COVID-19, we build an evaluation indicator system from four dimensions: technology, instructor, learner and environment including, 10 indicators and 94 sub-indicators. Secondly, the cloud model is used to quantitatively describe the natural language and uncertainty in a large amount of assessment information. The cloud model generator is used for sub-indicators and achieves an effective and flexible conversion between linguistic information and quantitative values. The cloud model of indicators are presented by integrating the corresponding sub-indicators. The weights of indicators are determined by the entropy method based on the cloud model and possibility degree matrix, which eliminates the judgment of decision-makers and has great power for handling practical problems with unknown weight information. Finally, a fuzzy TOPSIS method based on the cloud model is proposed to rank the satisfaction of online education of different colleges. The proposed method is compared with other existing methods to shown its merits. The experimental result is consistent with the proportion of students who accept online education in the post-epidemic era. According to the second questionnaire, as the qualitative evaluation of the cloud model of indicators increases, the qualitative evaluation of satisfaction of different types of colleges will also increase. It indicates that the method proposed in this paper is practical.

Research on the fire safety assessment of high building with intuitionistic fuzzy TOPSIS method

In our country, fire from high-rise buildings happens from time to time and produced economic loss could be well over 100 billion that will give rise to great harm to safety of the people’s life and property even to the development of the whole national economy. In the fire protection work for High-rise building’s safety assessment, prevention, cause and salvation, all of this controlled by multiple factors. With their different attributes, fire problem and management work became more complex and even harder. When we want to integration and judgment the information which including many main bodies that with multi-aspect and evaluation index characteristics to be evaluated, Fuzzy mathematics evaluation method can help us. It can consider fully the fuzzy and uncertain in the assessment. For the problems in high-rise Building fire protection management. And it is frequently viewed as a multi-attribute group decision-making (MAGDM) issue. Thus, a novel MAGDM method is needed to tackle it. Depending on the conventional TOPSIS (Technique for Order Preferenceby Similarity to Ideal Solution) method and intuitionistic fuzzy sets (IFSs), this essay designs a novel intuitive distance based IF-TOPSIS method for fire safety assessment based on the high building. Afterwards, relying on novel distance measures between IFNs, the conventional TOPSIS method is extended to the intuitionistic fuzzy environment to calculate assessment score of each alternative. Eventually, an application about fire safety assessment based on the high building and some comparative analysis have been given to demonstrate the superiority of the designed method. The results illustrate that the designed framework is useful for fire safety assessment based on the high building.

SUPPLIER SELECTION AMONG DIFFERENT SCALE CONSTRUCTION COMPANIES USING FUZZY AHP AND FUZZY TOPSIS

Supplier selection is an important strategic decision for construction companies due to long-term project durations and high costs. In the construction sector, supplier selection decisions should take several criteria and alternatives into account. Along with the high number of alternative suppliers, choosing the best method to evaluate the alternative suppliers is another critical step. In this study, we compare the effectiveness of different multi-criteria decision‐making methods for selecting the most convenient supplier for construction companies. In this respect, we study the integration of powerful multi-criteria decision‐making methods, Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). We use Fuzzy AHP for the calculation of decision criteria weights, and then we apply Fuzzy TOPSIS for ranking the alternatives. Several interviews were made with the experts at construction companies and as a result of those interviews, 7 main criteria and 24 sub-criteria for comparing alternative suppliers of the companies were determined. We test our approach for two construction companies and use an integrated Fuzzy AHP and Fuzzy TOPSIS method to find the best supplier for the selected criteria. The contribution of this study is not limited to the multi-criteria decision-making methods for the supplier selection problem in the construction sector, but also we make a comparison of the supplier selection decisions of two different sized companies having the same supplier pool, and we show the effect of company based criteria weights in supplier selection.

Robot Selection Problem via Fuzzy TOPSIS Method Using Novel Distance and Similarity Measure for Generalized Fuzzy Numbers with Unequal Heights

Background: Mega multinational companies are highly dependent on robots to handle the maximum of their machinery workload, which significantly reduces human labor and saves valuable time as well. However, as vital as the role of robots is, a much more challenging task is its selection. Moreover, the robots need to be evaluated on the grounds of different specifications and their ease of handling, which results in a smooth and work-efficient environment. Objective: The prime objective of this paper is to devise a fruitful decision-making model for a robot selection problem, which utilizes a multi-criteria decision-making method known as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The TOPSIS method is based on the newly defined distance measure involving generalized fuzzy numbers with unequal heights (GFNUHs). Methodology/Approach: At first, we define a novel distance measure based on the “expected value” and “variance” of GFNUHs, where both the parameters are evaluated with the help of the [Formula: see text]-cut method. We then also give the expression for the distance-based similarity measure and investigate some of their properties. Both the distance and the similarity measure(s) are then validated for their effectiveness through a hypothetical case study of pattern recognition. Moreover, we consider 10 different bunches of generalized fuzzy numbers (GFNs) and present a comparative study with the already established measures to establish the efficiency and superiority of our proposed measures. Finally, the distance measure is deployed in the TOPSIS method, which facilitates suitable robot selection by an automobile company. Findings/Results: A comparison of results for the proposed distance measure and the similarity measure with the existing ones is presented which proves that the proposed measure(s) are effective and usable. Novelty/Value: The evaluation of expected value and variance of GFNUHs with the help of [Formula: see text]-cut technique is a completely original idea showcased in this paper and its improved version of TOPSIS for GFNUHs as discussed shall add a new direction in the realm of decision-making.

Manager selection using Fuzzy TOPSIS method

Due to increasing competition in the global market, companies need employees especially managers who are knowledgeable and skilful to compete in the world market. Proper selection of managers can ensure the accomplishment of company goals. This study aims to propose Fuzzy Technique for order preference by similarity to ideal solution (TOPSIS) method in hiring new personnel for the middle level manager position in a company. The aim of the study is to assess the alternatives and criteria weights for selecting the middle level manager in a company by using Fuzzy TOPSIS method. A real-life data about the middle level manager selection problem in a company is implemented to demonstrate the application of Fuzzy TOPSIS method. There are three decision makers, three selected alternatives (A1, A2, A3) and twelve chosen criteria in the study. The best alternative is the alternative which is close to fuzzy positive ideal solution (FPIS) and far from fuzzy negative ideal solution (FNIS). Other than that, the sensitivity analysis is performed to validate the results of the study by shifting the weight of each criterion to zero to check whether there is any influence on the final ranking of the alternatives. The findings showed that the ranking order is A1 > A2 > A3. This shows that A1 is the most preferable candidate for the middle level manager position in the company.

Multi-criteria decision making approaches to select appropriate enhanced oil recovery techniques in petroleum industries

To select the optimum methods, such criteria like reservoir heterogeneity, reservoir pressure, reservoir temperature, crude oil type API (American Petroleum Institute), and brine salinity. EOR methods contained water flooding, chemical flooding, nanofluids injection, CO2 (carbon dioxide) injection, SAGD/WAG (Surfactant assisted gas drainage/water alternative gas injection), and hybrid injection. Multi-criteria decision-making methods of FTOPSIS (a fuzzy technique for order preference by similarity to ideal solution) and FAHP (fuzzy analytic hierarchy process) were used to select the optimum in the EOR method. The hybrid injection is considered the preferable oil recovery enhancement method in both FTOPSIS and FAHP methods. It has a normalized weight of 74% and 23% for FTOPSIS and FAHP, respectively. In the FTOPSIS method, SAGD/WAG and CO2 methods are the second and third preferred enhanced oil recovery methods with the normalized weight of 65% and 56%, respectively. In the FAHP method, CO2 and SAGD/WAG methods are the second and third preferred enhanced oil recovery methods with the normalized weight of 19% and 14%.

A Framework to Evaluate Project Complexity Using the Fuzzy TOPSIS Method

This work aims to help managers anticipate, detect, and keep under control complex situations before facing negative consequences. This article explores complexity modeling theory and develops a framework and associated score sheet to measure project complexity. A framework comprising ninety factors is presented and divided into seven categories: stakeholders, project team, project governance, product, project characteristics, resources, and environment. For the project complexity assessment grid, the project manager prioritizes and weighs its factors using linguistic variables. The score sheet is customizable in its handling of the factors and their weights. A critical state of the art on multi-criteria methodologies is presented, as well as reasons for using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. This method provides early-warning signs with the possibility of comparing multiple projects. It also enables one to measure and prioritize areas and domains where complexity may have the highest impact. Practical applications on three projects within an automotive manufacturer highlight the benefits of such an approach for managers. Project managers could use both a project complexity rating system and a measure of risk criticality to decide on the level of proactive actions needed. This research work differs from traditional approaches that have linked proactive actions to risk criticality but not project complexity.

An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains

Digital supply chains (DSCs) are collaborative digital systems designed to quickly and efficiently move information, products, and services through global supply chains. The physical flow of products in traditional supply chains is replaced by the digital flow of information in DSCs. This digitalization has changed the conventional supplier selection processes. We propose an integrated and comprehensive fuzzy multicriteria model for supplier selection in DSCs. The proposed model integrates the fuzzy best-worst method (BWM) with the fuzzy multi-objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA), fuzzy complex proportional assessment of alternatives (COPRAS), and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The fuzzy BWM approach is used to measure the importance weights of the digital criteria. The fuzzy MULTIMOORA, fuzzy COPRAS, and fuzzy TOPSIS methods are used as prioritization methods to rank the suppliers. The maximize agreement heuristic (MAH) is used to aggregate the supplier rankings obtained from the prioritization methods into a consensus ranking. We present a real-world case study in a manufacturing company to demonstrate the applicability of the proposed method.

Pythagorean fuzzy TOPSIS method based on 2-tuple probability weight

In this paper, the concept of 2-tuple probability weight is presented, and on this basis, the technique for order preference by similarity to ideal solution (TOPSIS) method in Pythagorean fuzzy environment is given. First, the definition of 2-tuple probability weight is put forward, and two examples are provided to illustrate that 2-tuple probability weight can effectively prevent the loss of information. Second, the notion of real-value 2-tuple is defined for any two real numbers, and some basic operations, operation properties, and sorting functions are introduced. Finally, a 2-tuple probability weight Euclidean distance is provided, a new Pythagorean fuzzy TOPSIS method is further proposed, and the flexibility and effectiveness of the proposed methods are illustrated by an example and two comparative analyses.