Fuzzy Decision Analysis Research Articles

Context Based Ranking Strategies for Renowned Instructional Methodologies

The main objective of this work is to validate the decisions made towards adoption of appropriate instructional methodologies based on the context of a specific region considering the quality of education, the cost of education and the learning outcomes as predominant parameters. The non-deterministic events and uncertain situations that may arise over a long-range period impose a vague and fuzzy environment in the educational system. Investigations have been made to identify suitable educational framework for implementation in the institutions of a specific region in view of these unpredictable events and non-deterministic conditions. Fuzzy decision analysis and rough set theory have been applied to rank the prominent instructional methodologies which are encompassed within each educational framework. Hurwicz Rule is adopted to balance the pessimistic and optimistic opinions about the non-deterministic events while validating the merits of the instructional methodologies. Grey relational analysis is carried out while ranking instructional methodologies in a vague environment. In this work, the instructional methodologies are ranked using fuzzy entropy as well as crisp entropy measures and the outcomes of the fuzzy and rough sets-based decision analysis have been validated.

A Fuzzy PROMETHEE Method for Evaluating Strategies towards a Cross-Country Renewable Energy Cooperation: The Cases of Egypt and Morocco

Recognising the urgency of addressing climate change and the imperative to mitigate its effects, the European Union (EU) has embarked on a transformative journey to reshape its energy landscape, with a pronounced emphasis on harnessing renewable energy sources (RESs) and augmenting their contribution to electricity generation. To propel Europe towards sustainable development through its energy transition, EU member states are encouraged to foster collaborative efforts on a European scale, inviting neighbouring countries to participate in joint ventures aimed at leveraging RESs for electricity generation. Consequently, it becomes imperative to evaluate the potential depth of cooperation among these nations, assessing how such partnerships can align with Europe’s overarching objectives while fostering mutually beneficial conditions. This paper seeks to undertake a thorough analysis and evaluation of the potential impacts of such cooperation, both in advancing RES objectives and in promoting broader cooperation goals concerning the countries involved. The appropriate methodological framework has been developed, utilising and implementing the fuzzy PROMETHEE multicriteria decision analysis method, to address the problem’s multidimensional character, intending to implement an appropriate action plan and promote production from RESs. The methodology has been applied to assess alternative strategies in two case study countries, Morocco and Egypt, while important outcomes have emerged towards the successful implementation of cooperation mechanisms promoting RES.

Application of Remote Sensing and Spatial Fuzzy Multi-criteria Decision Analysis to Identify Potential Dust Sources in Lake Urmia Basin, Northwest Iran

Application of Remote Sensing and Spatial Fuzzy Multi-criteria Decision Analysis to Identify Potential Dust Sources in Lake Urmia Basin, Northwest Iran

An ecotourism suitability index for a world heritage city using GIS-multi criteria decision analysis techniques

The concept of ecotourism has experienced a significant surge in popularity over the past two decades, primarily driven by the multitude of adverse impacts associated with mass tourism. The objective of the study was to develop a comprehensive ecotourism suitability index to guide policymakers in implementing tourism development policies. Given the considerable appeal of the study area to both local and international tourists, it is essential to conduct a systematic evaluation to pinpoint suitable areas for ecotourism development. This necessity arises from the study area's placement within a fragile ecosystem and its proximity to a UNESCO World Heritage site. We employed a Geographic Information Systems (GIS) integrated environment coupled with a fuzzy Multi-Criteria Decision Analysis (MCDA) methodology. The GIS-MCDA integrated framework leverages the Analytic Hierarchy Process (AHP) and a weighted linear combination that seeks to amalgamate many features and criteria to assess ecotourism potential by integrating 20 criteria into six separate categories: landscape, topography, accessibility, climate, forest and wildlife, and negative factors. Weights were allocated to each criterion and factor based on the expert's opinions of their impact on the development of ecotourism. The final ecotourism suitability index comprised five unique classes: very high, high, moderate, less, and not suitable. Results reveal that out of the total areas, 45.4 % (259 km2) are within the high and very high suitable classes. The sensitivity analysis suggested that ecotourism potentials are more favorable to forest and accessibility variables. The generated index can be utilized as a road map since validation verified a 64 % accuracy. Given the dearth of earlier research, this study provides vital support for the development of sustainable ecotourism projects in the study area.

Location selection for waste disposal boxes: a geographic information systems based Pythagorean fuzzy multi-criteria decision analysis

Location selection for waste disposal boxes: a geographic information systems based Pythagorean fuzzy multi-criteria decision analysis

Aczel-Alsina power bonferroni aggregation operators for picture fuzzy information and decision analysis

Picture fuzzy set (PFS) is an expedient mathematical approach for interpreting imprecise and nebulous information, and the power Bonferroni mean (PBM) operator is a crucial generalization of the power average (PA) operator, and the Bonferroni mean (BM) operator. Based on the Aczel-Alsina (AA), operational principles of PFS, we expand the PBM operator to integrate PFVs and develop a few AOs, namely PF Aczel-Alsina PBM (PFAAPBM) operator, weighted PF Aczel-Alsina PBM (WPFAAPBM) operator, PF Aczel-Alsina PGBM (PFAAPGBM) operator, and weighted geometric PF Aczel-Alsina PBM (WGPFAAPBM) operators respectively. These newly suggested PF Aczel-Alsina PBM operators can detect the connections between the membership, abstinence, and non-membership functions, which also maintain the important characteristics of the PBM operator. After that, we analyze a few enticing characteristics along with the particular applications of the suggested operators. Based on our suggested technique, we built an illustrated numerical example for the selection of competent research scientists to cope with MADM issues under the framework of PFVs. Finally, we contrast a few of our suggested methodologies with other prevailing methods to determine the feasibility and legitimacy of our suggested strategies.

A comprehensive decision assessment for trust evaluation in wireless sensor networks

Objective: This study endeavors to tackle the pressing issue of network security within Wireless Sensor Networks (WSNs) through the introduction of an innovative integrated Pythagorean fuzzy-based method for evaluating network nodes. The primary aim is to enrich decision making frameworks within WSNs by furnishing a robust methodology for identifying and eradicating malevolent nodes. Methods: investigation employs an integrated Pythagorean fuzzy-based methodology to appraise network nodes by scrutinizing specific trust attributes. Comparative assessment with alternative contemporary Multiple Criteria Decision Making (MCDM) trust models is conducted to gauge the effectiveness of the proposed strategy. Results: The results underscore the efficacy of the integrated Pythagorean fuzzy-based approach in bolstering network security through the precise identification and elimination of malicious nodes. Comparative analysis with other MCDM trust models highlights the superiority of the proposed approach in evaluating network nodes based on trust attributes. Recommendations: In light of the findings, it is advised to integrate fuzzy decision analysis methodologies into decision making systems for WSNs to enhance network security. Additionally, future research endeavors could concentrate on refining and expanding upon the proposed methodology to effectively address emerging security challenges within WSNs.

Commercial Aircraft Selection Decision Support Model Using Fuzzy Combinative Multiple Criteria Decision Making Analysis

Multidimensional decision-making issues invariably entail a profusion of factors and dimensions necessitating consideration. In such intricate environments, decision-making can be notably challenging. To navigate this complexity, the realm of multiple criteria decision-making approaches is indispensable, helping in unraveling convoluted predicaments. This paper introduces a novel approach fuzzy combinative multiple criteria decision-making analysis — crafted to address fuzzy decision analysis challenges. At the heart of this method lies the utilization of the Euclidean distance as the primary measure and the rectilinear distance as the secondary measure, both calibrated in accordance with the negative-ideal solution. Determining the desirability of alternatives rests on these distances. Further augmenting the evaluation, the process involves combining the Euclidean and rectilinear distances through fuzzy combinative multiple criteria decision-making analysis. The efficacy and stability of the fuzzy decision analysis are underscored through a numerical example, illustrating the proposed method's procedural nuances. A comparative analysis comparing both Euclidean distance and rectilinear distance with the weighted sum model and the weighted product model is also conducted. This scrutiny underscores the efficiency of the proposed method while affirming the reliability of its outcomes.

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.

Understanding the exchange process between ground and surface water using mini drive point piezometer and mathematical models to identify suitable managed aquifer recharge sites.

In the current study, subsurface characteristics within the complex formation of the Shilabati basin system of West Bengal, India, extending over an area of 3888 km2, have been estimated using a cost-effective piezometer and MIKE FEFLOW package based on a steady-state numerical model. Pore size and fine particle content of streambeds are affected by two opposing flow contraptions. Such opposite flow conditions are likely to affect the hydraulic conductivity of the streambed. However, analogies of the hydraulic conductivity (Kh) of streambeds for losing and gaining streams have not been well documented in the recent past. The Kh value from the piezometer has been highest at the Dakshin Pairachali site (6.765 m/day), with the stream gaining water from the discharge of the local aquifer. Analysis of the stream-aquifer interaction using the FEFLOW model has allowed us to understand the groundwater water head of the basin ranging from 160.33 to 0.32 m.a.s.l (meters above sea level). The present study also constitutes the first attempt for the identification of suitable sites for the implementation of managed aquifer recharge (MAR) technology in West Bengal, India, to manage extreme drought events. The suitable sites have been identified by means of three fuzzy multi-criteria decision analysis based on nine criteria: river discharge, moisture content, porosity, drainage type, rainfall, land use type, geology, aquifer material, and hydraulic conductivity. To design a radial collector well and infiltration gallery for the selected site in an anisotropic, homogeneous, unconfined, and semi-infinite aquifer near a fully penetrating stream, a pumping test has been conducted to optimize a safe yield of 12.096 MLD (megaliters per day).

Extended MABAC method based on 2-tuple linguistic $ T $-spherical fuzzy sets and Heronian mean operators: An application to alternative fuel selection

<abstract><p>In recent years, fossil fuel resources have become increasingly rare and caused a variety of problems, with a global impact on economy, society and environment. To tackle this challenge, we must promote the development and diffusion of alternative fuel technologies. The use of cleaner fuels can reduce not only economic cost but also the emission of gaseous pollutants that deplete the ozone layer and accelerate global warming. To select an optimal alternative fuel, different fuzzy decision analysis methodologies can be utilized. In comparison to other extensions of fuzzy sets, the $ T $-spherical fuzzy set is an emerging tool to cope with uncertainty by quantifying acceptance, abstention and rejection jointly. It provides a general framework to unify various fuzzy models including fuzzy sets, picture fuzzy sets, spherical fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets and generalized orthopair fuzzy sets. Meanwhile, decision makers prefer to employ linguistic terms when expressing qualitative evaluation in real-life applications. In view of these facts, we develop an extended multi-attributive border approximation area comparison (MABAC) method for solving multiple attribute group decision-making problems in this study. Firstly, the combination of $ T $-spherical fuzzy sets with 2-tuple linguistic representation is presented, which provides a general framework for expressing and computing qualitative evaluation. Secondly, we put forward four kinds of 2-tuple linguistic $ T $-spherical fuzzy aggregation operators by considering the Heronian mean operator. We investigate some fundamental properties of the proposed 2-tuple linguistic $ T $-spherical fuzzy aggregation operators. Lastly, an extended MABAC method based on the 2-tuple linguistic $ T $-spherical fuzzy generalized weighted Heronian mean and the 2-tuple linguistic $ T $-spherical fuzzy weighted geometric Heronian mean operators is developed. For illustration, a case study on fuel technology selection with 2-tuple linguistic $ T $-spherical fuzzy information is also conducted. Moreover, we show the validity and feasibility of our approach by comparing it with several existing approaches.</p></abstract>

Evaluate Ho Chi Minh City Sustainability Using Fuzzy Extent Analysis Method

Sustainable development of cities was among the goals aimed by either country or region since the 1980s. Ho Chi Minh City was ranked as the most rapid urban development in Vietnam, which challenged the accommodation of the necessities for a pleasant life in a city with limited resources, including housing, public infrastructure, a clean environment, security, safety, employment, and other necessities. The purpose of this study was to measure city sustainability by employing fuzzy decision analysis. A systematic review of the literature has provided the theoretical framework for measuring sustainable cities. Further consent on the criteria of a sustainable city in the context of Ho Chi Minh City, Vietnam was confirmed based on the evaluation of thirty experts with academic and practical experience in the field. The research findings provided the measurement model of city sustainability at three levels with three main criteria at 2nd level and twenty sub-criteria at 3rd level. The research results revealed that there is great consent for city performance and priority ranking in terms of the social dimension. However, great conflict in the importance and performance of economic and environmental dimensions has been found. This practically implied the strategies for bridging the gap between the city’s actual criteria performance and priority ranking in target city sustainability.

An extended picture fuzzy multicriteria group decision analysis with different weights: A case study of COVID-19 vaccine allocation

The high contagion rates of COVID-19 and the limited amounts of vaccines forced public health authorities to develop vaccinations strategies for minimizing mortality, avoiding the collapse of health care infrastructure, and reducing their negative impacts to societies and economies. We propose a Multi Criteria Group Decision Making for prioritizing a set of COVID-19 vaccination alternatives, under a picture fuzzy environment, where the weights for Decisions Experts (DE) and criteria are unknown. A panel of six DEs assess six criteria for prioritizing four groups for vaccination. The weights for DE and criteria are handled in the form of fuzzy sets. Three types of weights are calculated: subjective, objective, and mixture weights.According to our results, three out of the six criteria hold 60% of the strategic importance: 1) allocation and distribution, 2) COVID-19 strains and 3) capabilities and infrastructures. However, persons with comorbidities became the group with the highest priority, followed by essential workers, women, and adults older than 40 years. Governments, decision makers, and policy makers can find rigorous scientific evidence for articulating effective vaccinations campaigns from this work, and contribute to minimize undesired outputs, such as high mortality rates or collapse of hospitals.

A New Self-Assessment “TQM Hybrid MCDM Fuzzy Model” For Enhancing the KPIs in Mega Universities

The key performance indicators (KPIs) are an effective part of benchmarking for measuring the performance of universities aiming to raise the university quality services level. The problem is that there is no general standard analytical evaluation model for assessing KPIs criteria in higher education institutes for evaluating mega universities, and there are inadequacies in the treatment of specific current educational quality standards. In this paper, a hybrid fuzzy analytical model for TQM self-assessment to enhance KPIs in mega universities is proposed. The proposed model produces important weights for TQM-KPIs that are recommended for helping higher authorities at the university for enhancing the demanded total quality services and aid the university to achieve its strategic objectives and to be one of the highly ranked universities. In addition, the European Foundation for Quality Management (EFQM) excellence model enabler criteria were modified and used. Two additional enabler criteria for representing the mega university and the world ranking were proposed. The “TQM Hybrid Fuzzy Model” proposed integrates three fuzzy multiple criteria decision-making (MCDM) submodels including (1) the fuzzy analytic hierarchy process (FAHP), (2) the fuzzy decision-making trial and evaluation laboratory (FDEMATEL), and (3) the fuzzy multiple criteria decision analysis (FVIKOR). Each of these submodels is computed and evaluated analytically. A comparison between them is achieved. Finally, the whole “TQM Hybrid F-MCDM Model” proposed is proved and evaluated analytically and programmed using Excel. Hence, by comparison, it is found that the proposed hybrid fuzzy model is the most effective model for evaluating the TQM-KPIs for enhancing mega universities’ organizational assessment. Results show that the subcriteria that occupied the first three positions are the managed and improved distance learning sources and materials, policy, and strategies that are based on the present and future needs and expectations of stakeholders.

Comparison of hospital service performances under COVID-19 pandemics for pilot regions with low vaccination rates

It is essential to measure the quality and performance of health centers and propose policies in order for health services to continue without interruption during the pandemic period and for the continuous and proper implementation of new procedures in hospitals with COVID-19.The measurement of service quality and performance in hospitals should be provided not only for the smooth flow of health services that are vital for individuals but also for the elimination of hesitations in the treatment and vaccination processes related to COVID-19. Previously, models have been proposed by introducing some criteria to measure and evaluate hospital service performance in some extraordinary conditions, but such a study has not yet been put forward under pandemic conditions. Starting from this point, we aim to fill the gap in the literature by conducting a measurement study for hospitals in the pilot region, where COVID-19 cases are common but vaccination is observed at low rates. For this aim, the evaluation criteria are gathered under basic dimensions as in SERVPERF (Service Performance), which is a widely used tool for measuring service quality and a fuzzy multi-criteria decision analysis is proposed to measure the service performance of state hospitals for a pilot region. In the proposed methodology, the integrated methods consisting of CRITIC-TOPSIS have been extended with fermatean fuzzy sets. Expert opinions are taken via questionaries to determine hospital service performances. Based on the results obtained from the hospitals in the pilot region, the policies and strategies to be adopted by the hospitals serving under pandemic conditions worldwide to increase the service quality have been put forward. Additionally, the sensitivity of the parameters in the problem is measured, and then the validity of the obtained results is also validated. According to the results, assurance is determined as the most important main service performance factor during the pandemic period. So, the managers should develop strategies to address people's concerns about vaccines and increase people's trust in hospitals.

Ranking of Independent and Dependent Fuzzy Numbers and Intransitivity in Fuzzy MCDA

Ranking of fuzzy numbers (FNs) is a key stage within fuzzy multicriteria decision analysis (FMCDA). However, the influence of FNs dependence on their ranking, including ranking alternatives within FMCDA, has not been studied yet. In this article, for studying such an influence, the widely used defuzzification-based fuzzy ranking methods, centroid index, and integral of means, along with their modifications, which are pairwise comparison defuzzification ranking methods, are explored. The authors argue that classical defuzzification ranking methods are intended to deal with independent FNs, whereas their modifications may be used for ranking of dependent FNs. It is provided a proof in which, pairwise comparison Yuan’s and defuzzification integral of means ranking methods, are equivalent when ordering independent and can differ when ordering dependent FNs; at the same time, Yuan’s and modified integral of means ranking methods are equivalent when ordering both independent and dependent FNs. Intransitivity of the two modified ranking methods when ordering dependent FNs as well as intransitivity of alternatives in FMCDA for fuzzy multiattribute value theory (FMAVT) as an example is proved. The distinctions in ranking of dependent FNs by all ranking methods under consideration are explored through ordering alternatives within FMAVT. For this, a real-life case study is considered, and the distinctions in ordering alternatives by classical and modified ranking methods are demonstrated. Statistical analysis of distinctions in ordering alternatives by FMAVT with different ranking methods is implemented with the use of Monte–Carlo simulation. The significance of distinctions for the choice and ranking multicriteria problems, as well as for justification of utilizing ranking methods under consideration in FMCDA, is discussed.

Multicriteria q-Rung orthopair fuzzy decision analysis: a novel approach based on Archimedean aggregation operators with the confidence levels

The confidence levels can reduce the influence of the unreasonable evaluation value that was given by the decision-maker on the decision-making results. The Archimedean t-norm and t-conorm (ATS) also have many advantages for the processing of uncertain data. Under this environment, the confidence q-rung orthopair fuzzy aggregation operator based on ATS is one of the most successful extensions of confidence q-rung orthopair fuzzy numbers in which we decrease the deviation caused by the subjective perspective of the decision-maker in the multicriteria group decision-making problems. In this paper, we propose weighted, ordered weighted averaging aggregation operators and weighted, ordered weighted geometric aggregation operators based on ATS, respectively. Moreover, the properties and four specific forms associated with aggregation operators are also investigated. In this study, a novel MCGDM approach is introduced by using the proposed operator. A reasonable example is proposed and compared the results that are obtained by our operators and that in the existing literature, so as to verify the rationality and flexible of our method. From the study, we concluded that the proposed method can reduce the impact of extreme data, and make decision-making results more reasonable by considering the attitudes of decision-makers.

Customer-oriented product design using an integrated neutrosophic AHP & DEMATEL & QFD methodology

With the increasing product variety, companies aim to become better than their competitors by providing a superior product developed with a customer-oriented product design approach and a quality strategy. In order to achieve this, companies should well understand customer expectations and quickly be able to convert these expectations to technical characteristics. Since the expectations consist of mostly subjective judgments, this evaluation process contains vagueness and impreciseness. A triplet represents the uncertainty in subjective judgments: the degrees of belongingness or Truthiness (T), non-belongingness or Falsity (F), and indeterminacy (I). For this reason, in this paper, a neutrosophic Quality Function Deployment (QFD) methodology based on neutrosophic AHP and neutrosophic DEMATEL is developed and applied to the design of a car seat. In this methodology, the weighting of customer requirements is performed by neutrosophic AHP. The relationships among the technical characteristics are determined by neutrosophic DEMATEL for the customer-oriented product design, considering both impreciseness in the data and indeterminacy of the decision-makers. In other words, the contribution of this paper is that the proposed methodology provides better integration of the voice of customers into technical characteristics through a practical fuzzy multi-criteria decision analysis. Based on the results, it is revealed that seat height is the most important technical characteristic, followed by vertical travel range and horizontal travel range. Moreover, validity and verification of the proposed methodology have been tested with other methods presented in the literature. Sensitivity analyses have been carried out to show the flexibility of the given decisions under different cases. Lastly, possible implications on theoretical and managerial aspects have been discussed.

Interval‐Valued q‐Rung Orthopair Fuzzy QUALIFLEX Decision Analysis Method with Dombi Operators

As a new and useful decision tool, interval‐valued q‐rung orthopair fuzzy set (IVq‐ROFS), has strong ability to address uncertain or imprecision information in practical decision‐making processes. This paper develops a new interval‐valued q‐rung orthopair fuzzy QUALIFLEX decision analysis method with Dombi operators for handling the group decision‐making problems with IVq‐ROFSs data. We also conduct a case study on the health management of hypertensive patients for demonstrating the feasibility and superiority of the developed method. The main contributions of this paper are as follows: (1) we first propose interval‐valued q‐rung orthopair fuzzy Dombi operational laws and investigate their desirable properties; (2) using the developed Dombi operational laws, we develop an interval‐valued q‐rung orthopair fuzzy Dombi weighted average (IVq‐ROFDWA) operator, and we prove that the IVq‐ROFDWA operator satisfies the properties of idempotency, commutativity, boundedness, and monotonicity; (3) we introduce the concept of interval‐valued q‐rung orthopair fuzzy ideal group opinions with the help of IVq‐ROFDWA operator and propose a new weight‐determining method for identifying the weights of experts; (4) we develop a new interval‐valued q‐rung orthopair fuzzy distance measure. With the help of the developed distance measure, we calculate interval‐valued q‐rung orthopair fuzzy concordance/discordance index under each permutation, and then a new interval‐valued q‐rung orthopair fuzzy QUALIFLEX decision analysis method is developed for addressing the complex multiattribute group decision‐making problems with IVq‐ROFSs.

Uncertain Multi-Criteria analysis of offshore wind farms projects investments – Case study of the Polish Economic Zone of the Baltic Sea

Investments in offshore wind farms can be an effective development stimulus for an economy recovering from the crisis caused by the COVID-19 pandemic. Therefore, an important issue is a multi-criteria analysis of planned investments in offshore wind farms. Such an analysis allows to identify the most important projects from the perspective of sustainable development. Taking into account the uncertainties and risks related to wind energy, and additionally taking into account the uncertainty of ex-ante evaluation, such studies need to analyse the uncertainty as widely as possible. The article presents a comprehensive methodological approach that allows for the maximum capture of uncertainties and risks related to energy investment projects in the area of wind farms. This approach involves using the fuzzy multi-criteria decision analysis (FMCDA) method, sensitivity analysis and robustness analysis based on the Monte-Carlo simulations. Additionally, the uncertainty related to the applied methodology was taken into account and the same problem was solved by using different FMCDA methods. Based on the applied approach, a case study was conducted and a ranking of offshore wind farms projects in Poland was created. It was found that the most promising project is Bałtyk II, followed by Bałtyk I, both projects being carried out by the Polenergia/Equinor consortium. However, if the preference model is not known, the Bałtyk I project has the greatest chance of taking the leasing place in the ranking (31.7%), ahead of the following projects: Baltic Power (20.4%) owned by PKN Orlen and Bałtyk III (18.6%) which is also owned by Polenergia/Equinor.