Multiple criteria decision-making (MCDM) is considered as a complex decision-making (DM) tool involving both quantitative and qualitative factors. In recent years, several MCDM techniques and approaches have been suggested to choosing the optimal probable options. The purpose of this article is to systematically review the applications and methodologies of the MCDM techniques and approaches. This study reviewed a total of 393 articles published from 2000 to 2014 in more than 120 peer reviewed journals (extracted from Web of Science). According to experts’ opinion, these articles were grouped into 15 fields. Furthermore, these articles were categorised based on authors, publication date, name of journals, methods, tools, and type of research (MCDM utilising research, MCDM developing research, and MCDM proposing research). The results of this study indicated that in 2013 scholars have published articles more than in other years. In addition, the analytic hierarchy process (AHP) method in the individual tool...

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Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014

Fuzzy best-worst method is proposed to solve the issues under fuzzy environment.A consistency ratio for fuzzy best-worst method is proposed for verification.The results indicate the fuzzy best-worst method outperforms best-worst method.The fuzzy best-worst method has a higher comparison consistency. Considering the vagueness frequently representing in decision data due to the lack of complete information and the ambiguity arising from the qualitative judgment of decision-makers, the crisp values of criteria may be inadequate to model the real-life multi-criteria decision-making (MCDM) issues. In this paper, the latest MCDM method, namely best-worst method (BWM) was extended to the fuzzy environment. The reference comparisons for the best criterion and for the worst criterion were described by linguistic terms of decision-makers, which can be expressed in triangular fuzzy numbers. Then, the graded mean integration representation (GMIR) method was employed to calculate the weights of criteria and alternatives with respect to different criteria under fuzzy environment. According to the concept of BWM, the nonlinearly constrained optimization problem was built for determining the fuzzy weights of criteria and alternatives with respect to different criteria. The fuzzy ranking scores of alternatives can be derived from the fuzzy weights of alternatives with respect to different criteria multiplied by fuzzy weights of the corresponding criteria, and then the crisp ranking score of alternatives can be calculated by employing GMIR method for optimal alternative selection. Meanwhile, the consistency ratio was proposed for fuzzy BWM to check the reliability of fuzzy preference comparisons. Three case studies were performed to illustrate the effectiveness and feasibility of the proposed fuzzy BWM. The results indicate the proposed fuzzy BWM can not only obtain reasonable preference ranking for alternatives but also has higher comparison consistency than the BWM.

Fuzzy best-worst multi-criteria decision-making method and its applications

In recent years, with the advent of globalization, the world is witnessing a steep rise in its energy consumption. The world is transforming itself into an industrial and knowledge society from an agricultural one which in turn makes the growth, energy intensive resulting in emissions. Energy modeling and energy planning is vital for the future economic prosperity and environmental security. Soft computing techniques such as fuzzy logic, neural networks, genetic algorithms are being adopted in energy modeling to precisely map the energy systems. In this paper, an attempt has been made to review the applications of fuzzy logic based models in renewable energy systems namely solar, wind, bio-energy, micro-grid and hybrid applications. It is found that fuzzy based models are extensively used in recent years for site assessment, for installing of photovoltaic/wind farms, power point tracking in solar photovoltaic/wind, optimization among conflicting criteria. The review indicates that fuzzy based models provide realistic estimates.

Applications of fuzzy logic in renewable energy systems – A review

Multi-criteria decision making (MCDM) methods are becoming increasingly popular in solving energy selection problems because these problems involve multiple and often conflicting criteria. This paper presents comparative analysis of ranking renewable energy sources (RES) for electricity generation in Taiwan using four MCDM methods - WSM, VIKOR, TOPSIS, and ELECTRE. The Shannon entropy weight method is used to assess the importance of each criterion for the ranking of RES. After that, four MCDM methods are utilized for quantitative evaluation to rank all available RE alternatives. From the weights estimation results, efficiency is the first priority in all evaluation criteria, followed by job creation, operation, and maintenance cost. The purpose of this study is to rank the priorities of various RES and propose recommendations for Taiwan's RE development. The ranking results show that hydro is the best alternative in Taiwan, followed by solar, wind, biomass and geothermal. Furthermore, sensitivity analysis of the weights was conducted considering the ranking results heavily depend on the criteria weight. The results of sensitivity analysis indicated that when financial or technical aspects are focused upon, hydropower is the best RES because its technology is the most mature and the cost is the lowest in Taiwan. In addition, from an environmental perspective, wind energy is the best choice, and from the social perspective, solar PV is the best choice. The findings of this study can provide useful information to energy decision makers and serve as a reference for Taiwan's energy policy.

Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan

One of the problems facing researchers in the application of renewable energy systems is that the evaluation of the sustainability is extremely perplex. Decision making in energy projects requires consideration of technical, economic, environmental and social impacts and is often complicated. This paper presents a review of the current state of the art in decision support methods applied to renewable and sustainable energy throughout the literature in the field of energy planning. The selected papers were classified by their year of publication, decision making technique, energy type, the criteria used, geographic distribution and the application areas.

Decision making in renewable energy investments: A review

Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey

In this study, it is examined that the economics of the efficient of level 2 regions according to criterion of Statistical Regional Units Classification or Nomenclature of Territorial Units for Statistics (NUTS) in

https://dergipark.org.tr/tr/download/article-file/46275

Türkiye’de İstatistiki Bölge Birimleri Sınıflamasına Göre Düzey 2 Bölgelerinin Ekonomik Etkinliklerinin DEA Yöntemi ile Belirlenmesi ve Tobit Model Uygulaması

Sosyal, cevresel, yapisal, politik v.b. soyut faktorlerin oldugu ve kisitli butcenin en iyi sekilde kullanilmasinin zorunlu oldugu kamu hizmet sektorunde ihtiyaca gore secim yapilmasi problemiyle sik sik karsilasilir. Cok kriterli karar verme tekniklerinden, Analitik Hiyerarsi Prosesi (AHP), birden cok kriter iceren bu tur problemlerin cozumunde kullanilan bir karar verme yontemidir. Bu calismada belediyelerin toplu tasima arac secim problemi ele alinarak ikili karsilastirma yargilarindaki sozel belirsizligi daha iyi ifade etmek amaciyla Bulanik Analitik Hiyerarsi Prosesi tekniklerinden biri olan Chang’in Mertebe Analiz Yontemi kullanilmistir. Bulanik sayilari siralamak icin ise Kareli Ortalama ve Kwong-Bai yontemi kullanilarak alternatifler arasinda siralama yapilmistir.

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Bulanık AHP ile belediyelerin toplu taşıma araç seçimi

Technological developments resulted in creative, faster, target-oriented and knowledge-based marketing strategies more prone to interactions. Digital marketing is an example of marketing types arisen by technological developments. Digital marketing tools are rapidly growing since they can be performed through internet; they are faster and thus have an ascending trend. The amount of investment to be made to each digital marketing tool has become a significant decision making problems for the businesses. In this chapter, Fuzzy AHP and Fuzzy TOPSIS techniques were employed for the selection of digital marketing tools. Multi-criteria analysis revealed the Remarketing advertising as the most suitable digital marketing tool. Additionally, the social media advertising, advertising-per-impression, advertising-perclick, affiliate advertising, banner marketing and email-advertising were respectively found to be as the other significant marketing tools.

Selection of Digital Marketing Tools Using Fuzzy AHP-Fuzzy TOPSIS

Supplier selection decisions require the choices of individual purchases to determine products and order quantities from certain suppliers. When suppliers are evaluated according to well-defined criteria, their level of effort and attention to detail is expected to increase significantly. This can provide to improve productivity. So, determination of supplier selection criteria that is a multi-criteria decision making process can include both quantitative and qualitative elements that are very important. In this article, the aim is to offer a fuzzy decision making method to determine leading criteria, in terms of supplier selection for an automobile company that operates in Iran, because the right suppliers that are selected according to well-defined criteria can significantly reduce the material purchasing costs and improve corporate competitiveness. For that purpose, linguistic values are used for expressing fuzzy numbers in order to assess the ratings and weights of these factors by considering criteria such as the decisions made by people who work in the purchasing department of the company. Afterward, the fuzzy TOPSIS method that is a multiple criteria decision making (MCDM) method according to fuzzy set theory is presented to cope with the determination of supplier selection criteria process. According to the results, it is determined that the following are important for supplier selection criteria for automobile firms: delivery, the amount of past business, reciprocal arrangements, warranties, and geographical location.

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Ümran Şengül

Papers

Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey

Türkiye’de İstatistiki Bölge Birimleri Sınıflamasına Göre Düzey 2 Bölgelerinin Ekonomik Etkinliklerinin DEA Yöntemi ile Belirlenmesi ve Tobit Model Uygulaması

Bulanık AHP ile belediyelerin toplu taşıma araç seçimi

Selection of Digital Marketing Tools Using Fuzzy AHP-Fuzzy TOPSIS

Determination of Extended Fuzzy TOPSIS Method of Criteria Leading to Supplier Selection for Industries