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Given its widespread potential and technological advancements, it is critical to use the greatest amount of wind power in reaching the 100% renewable energy target in power grids. SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis is frequently used to evaluate alternative strategies in multi-criteria decision issues. This paper employs a hybrid Fuzzy Analytic Network Process (FANP) approach based on SWOT to assess the future development of wind power capacities in Turkey in light of the sectoral effects of the Covid-19 outbreak in 2020. To validate the proposed approach, the results are compared to the results of the SWOT-based Analytic Network Process (ANP), Analytic Hierarchy Process (AHP), and fuzzy AHP (FAHP). According to the findings, "Development of domestic and efficient technologies (ST1)" and "Sustaining support mechanisms in investments and technological research (SO2)" are the best alternative strategies in all analysis models. While the priority ranks of other alternative strategies are the same in AHP and FAHP hierarchical techniques, FANP differs from ANP when the linguistic assessment process is taken into account. This study proposes long-term strategies for increasing wind power capacity and sector sustainability, and it demonstrates that FANP could be an appropriate approach for prioritizing these strategies in current scenarios. [ABSTRACT FROM AUTHOR]

Likened to the economic calamity of World War Two, the COVID-19 pandemic has sparked fears of a deep economic crisis, killed more than six million people worldwide and had a ripple effect on all aspects of life. MCDM (multi-criteria decision making) methods have become increasingly popular in modeling COVID-19 problems owing to the multi-dimensionality of this crisis and the complexity of health and socio-economic systems. This paper is aimed to review 72 papers published in 37 leading peer-reviewed journals indexed in Web of Science that used MCDM methods in different areas of COVID-19 pandemic. In this paper, data retrieval follows the PRISMA protocol for systematic literature reviews. 35 countries have contributed to this multidisciplinary research and India is identified as the leading country in this field followed by Turkey and China. Also 36 articles, namely 50% of papers are presented in the form of international cooperation. " Applied Soft Computing " is the journal with the highest number of articles whereas "Journal of infection and public health" and " Operations Management Research " are ranked in the second place. The results indicate that AHP (including fuzzy AHP) is the most popular MCDM method applied in 37.5% of papers followed by TOPSIS and VIKOR. This review reveals that the use of MCDM methods is one of the most attractive research areas in the field of COVID-19. As a result, one of the main purposes of this work is to identify diverse applications of MCDM methods in the COVID-19 pandemic. Most studies i.e. 69% (49 papers) of the papers combined various fuzzy sets with MCDM methods to overcome the problem of uncertainty and ambiguity while analyzing information. Nevertheless, the main drawback of those papers has been the lack of theoretical justifications. In fact, fuzzy MCDM methods impose heavy computational load and there is no general consensus on the clear advantage of fuzzy methods over crisp methods in terms of the solution quality. We hope the researchers who applied fuzzy MCDM methods to COVID-19-related research understand the theoretical basis of MCDM methods and the serious challenges associated with basic operations of fuzzy numbers to avoid potential disadvantages. This paper contributes to the body of knowledge via suggesting a deep vision to critique the fuzzy MCDM methods from mathematical perspective. • We provide a literature review on peer-reviewed journal articles with high impact factor related to the application of MCDM methods in COVID-19 era. • A total of 72 articles are collected from 37 leading journals and categorized into 52 types of application. • We highlight some claims on fuzzy arithmetic which are at use in the fuzzy literature but having little theoretical support. [ABSTRACT FROM AUTHOR]

Ranking Intuitionistic Fuzzy Sets (IFS) using distance-based methods involves calculating the distance between an IFS and a reference point which represents either maximum (positive ideal solution) or minimum (negative ideal solution) value. These methods assume that similarity of an IFSs to the reference point increases as its distance from it decreases. While it is a common practice to use nonlinear distance functions for ranking IFSs, this paper proves that no nonlinear IF distance function can be robust. In this study, the shortcomings of the conventional procedure are demonstrated by providing a mathematical proof and an alternative ranking method based on the hypervolume metric is proposed. In addition, the suggested ranking approach is extended as a new multi-criteria decision making method called Hypervolume-based Evaluation and Ranking Technique (HEART). HEART is applied for multi-criteria assessment of Turkey's energy alternatives. Results are compared with three distance based multi-criteria decision making methods: TOPSIS, VIKOR, and CODAS. • The study uncovers the critical shortcomings of distance-based methods in ranking Intuitionistic Fuzzy Sets (IFS). • An alternative ranking method to distance based approaches, based on the hypervolume metric is proposed. • The hypervolume based ranking approach is extended for use in multi-criteria decision making problems. [ABSTRACT FROM AUTHOR]

Due to the increasing awareness of environmental, social and economic factors, solar photovoltaic (PV) system planning requires strategic decision making process for socio-economic development in many countries. The main objective of this paper is to propose a new Multi-Criteria Decision Making (MCDM) approach that is flexible and practical to the decision makers (DMs) in governments for solar PV panel manufacturer evaluation based on qualitative and quantitative factors. Accordingly, a novel two-stage MCDM model integrating Analytic Hierarchy Process (AHP) and Multiplicative Multi-Objective Ratio Analysis (MULTIMOORA) methods under Interval Valued Pythagorean Fuzzy (IVPF) environment is presented, and applied to select the most appropriate solar PV panel manufacturer for solar power plants in Southeastern Anatolia Region of Turkey. As a result, the proposed novel Integrated IVPF-AHP&MULTIMOORA method produces consistent and reasonable results to select the most appropriate solar PV panel manufacturer for the solar power plants in the cities of Southeastern Anatolia Region of Turkey considering some socio-economic sustainable indicators such as cost, environmental, efficiency and technical indices. Furthermore, sensitivity analysis and comparative analysis are also applied to prove the robustness and verification of the results of the proposed approach. • The most appropriate solar PV panel manufacturer is selected for solar plants in Southeastern Anatolia Region of Turkey. • A novel integrated MCDM methodology is presented in this paper. • The weights of criteria determined are obtained using IVPF-AHP. • The alternative solar PV panel manufacturers are evaluated by using IVPF-MULTIMOORA. • The proposed model provides socio-economic and environmental development of the region. [ABSTRACT FROM AUTHOR]

Söke Plain (Turkey) is one of the two plains where cotton production is the highest in Turkey, the leading country for cotton production in the Mediterranean Basin. The cropping pattern in Söke Plain is dominated by cotton with a ratio of 97%. The overall irrigation scheme is equipped with conventional systems (i.e., surface, furrow) whose efficiency is approximately 50% due to high evaporation and physical losses. Water efficiency improvement in cotton irrigation necessitates a thorough evaluation of the agricultural water management for Söke Plain, a water-scarce region under drought threat. In this paper, a hybrid multi-criteria decision making (MCDM) method is presented for the evaluation and selection of irrigation methods. This process involves various potentially conflicting qualitative and quantitative criteria, therefore, a hybrid MCDM method such as HF-AHP-PROMETHEE II is needed to make decisions. In HF-AHP-PROMETHEE II, "Hesitant Fuzzy Analytic Hierarchy Process" (HF-AHP) is first implemented to determine importance weights of criteria and then "Hesitant Fuzzy Preference Ranking Organization Method for Enriching Evaluations II" (HF-PROMETHEE II) is utilized to assess and rank the irrigation method alternatives. For comparison analysis, HF-AHP-TOPSIS (HF-AHP-Technique for Order Preference by Similarity to Ideal Solution) method is also implemented to the same problem. A case study is presented where five irrigation method alternatives in Söke Plain are assessed by five expert decision-makers (DMs), based on fifteen evaluation criteria. Sprinkler is found to be the first ranked irrigation method among five alternatives with both HF-AHP-PROMETHEE II and HF-AHP-TOPSIS resulting in the same ranking. The selection of this irrigation technique by the expert DMs is compliant with prevailing regional features related to hydrologic, climatic, environmental conditions and with regard to cotton, one of the highest water-consuming crops. • Söke Plain and surrounding area needs more efficient irrigation planning. • HF-AHP-PROMETHEE II and HF-AHP-TOPSIS methods are applied to evaluate irrigation methods in Söke. • irrigation methods are evaluated with 15 criteria by 5 decision-makers. • Sprinkler is ranked as the best irrigation method with both HF-AHP-PROMETHEE II and HF-AHP-TOPSIS. • Implementation of modern irrigation methods is necessary in the region. [ABSTRACT FROM AUTHOR]

• A novelty multi-criteria framework is proposed for bioenergy facility location. • This paper expands the scarce literature about bioenergy production in Turkey. • Analysis of bioenergy production and regulations is key to the bioenergy growth. • The bioenergy can contribute to complement the energy matrix of Turkey. Biofuels are rapidly taking their place amongst the renewable energy sources which are gaining importance day by day. Turkey procures a large portion of its energy needs with imported fossil fuels. This brings forward problems related to energy security and it also caused an increase in the greenhouse gas emissions of the country in the last decade. However, there are no satisfactory studies or investments related to biofuel potential and the evaluation of this potential. The research of the biomass energy potential in Turkey is of particular importance in terms of strengthening the energy policy. In this study, a multi-stage approach is presented for the first time in the appropriate site selecting for production facility to be established in a country. This is the most basic fact that distinguishes the study from other literature studies and makes it unique. Initially, the plant species and production amounts to be used in bioenergy production at the country scale were determined and theoretical biodiesel and bioethanol potentials were calculated. Then, the most suitable product-based site for the bioenergy production facility was determined with a hybrid method using the entropy-based multiple-attribute utility theory. Thus, contrary to the literature studies on potential determination only, the most suitable location for the bioenergy production facility was also selected by using determined potentials. The results show that Turkey has a biodiesel and bioethanol potential 1.666.176 tons, 13.546.751 tons, respectively. The products with the highest potential were determined for biodiesel and bioethanol production as sunflower (774.741 tons) and wheat (7.051.602 tons). [ABSTRACT FROM AUTHOR]