Assessment of Turkey's energy management performance via a hybrid multi-criteria decision-making methodology

Karataş, Mümtaz; Sulukan, Egemen; Karacan, İlknur

doi:10.1016/j.energy.2018.04.051

Cited by 29 publications

(10 citation statements)

References 63 publications

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“…Portfolio of RE sources for accomplishing the 3-E policy goals AHP Taiwan [11] RE and nuclear sources selection for electricity generation AHP Kazakhstan [12] Evaluating and selecting RE sources for electricity generation AHP Algeria [13] RE sources selection for sustainable electricity generation AHP Malaysia [14] Evaluating sustainable energy planning and management Fuzzy AHP India [15] The selection of RE alternatives for electricity production Fuzzy AHP Indonesia [16] Analyzing energy performance for sustainable development AHP-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) Turkey [17] Assessing the RE sources to accomplish policy scenario goals Fuzzy TOPSIS Europe [18] Analyzing and ranking the most efficient low-emission energy technologies Fuzzy AHP-Fuzzy TOPSIS Poland [19] Selection of wind power project locations AHP-Fuzzy TOPSIS Pakistan [20] Ranking the low-carbon energy sources AHP and TOPSIS China [21] Multi-criteria assessment of renewable micro-generation technologies TOPSIS, Evaluation Based on Distance from Average Solution (EDAS) and WASPAS Lithuania [22] It is determined from the literature that MCDA approaches greatly help in addressing and assessing sustainable energy planning problems. In this study, the fuzzy-based AHP and WASPAS methods have been applied because the fuzzy set theory is a valuable technique that helps in minimizing the uncertainty of the decision problem [23].…”

Section: Research Focus Research Methods Region Referencementioning

confidence: 99%

Analyzing Renewable Energy Sources of a Developing Country for Sustainable Development: An Integrated Fuzzy Based-Decision Methodology

et al. 2020

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Global human pollutant activities have raised greenhouse gas (GHG) emissions, which have directly affected the climate. Fossil fuel-based energy has brought a negative impact on the environment and is considered one of the largest sources of GHG emissions. It is envisaged that GHG emissions will increase in the future due to rapid population growth and industrialization. Thus, it is imperative to mitigate climate variability and reduce GHGs by adopting renewable energy (RE) sources for electricity generation. In this regard, the multi-criteria decision analysis (MCDA) process would serve the purpose of framing out energy policy to analyze these environmentally friendly energy sources. This study uses an integrated decision methodology—a combination of Delphi, fuzzy analytical hierarchy process (FAHP), and the fuzzy weighted aggregated sum product assessment (FWASPAS)—for the adoption of RE sources for electricity generation in Turkey. Initially, the study identified five main criteria and seventeen sub-criteria using the Delphi method. Then, the FAHP method was used to evaluate and rank the main criteria and sub-criteria. Finally, the FWASPAS method was used to assess and prioritize five major RE sources for electricity generation. The FAHP analysis indicated that political criteria are the most influential, followed by economic and technical criteria. Further, the FWASPAS method revealed that wind energy is the most significant option for electricity generation. This decision-making process can help the energy planners to utilize RE sources for sustainable development.

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Section: Research Focus Research Methods Region Referencementioning

confidence: 99%

Analyzing Renewable Energy Sources of a Developing Country for Sustainable Development: An Integrated Fuzzy Based-Decision Methodology

et al. 2020

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“…AHP and its extension fuzzy AHP methods are commonly utilized for different decision making problems such as manufacturing plant sustainability evaluation (Jayawickrama et al, 2017), mineral prospectivity mapping (Zhang et al, 2017), organ transplantation (Yuen, 2014), evaluation of in-flight service quality (Li et al, 2017) and shipping technology selection (Sahin and Yip, 2017). On the other hand, AHP and fuzzy AHP methods are applied with together another MCDM methods as shown in (Karatas, 2017;Otay et al, 2017;Karatas et al, 2018).…”

Section: Fuzzy Ahp Methodsmentioning

confidence: 99%

Otomotiv Endüstrisi için Bulanık Tabanlı Bir Yeşil Performans Değerlendirme Modeli

Çolak¹,

Boyacı²

2018

European Journal of Science and Technology

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Nowadays, increasing manufacturing activities cause to critical environmental problems such as global warming and air pollution. These environmental problems have provided increase of environmental awareness in the production process and therefore the green manufacturing (GM) concept has emerged. In general, this concept refers to a production process, which has high efficiency and minimum environmental damage in terms of resources and products. GM has recently become important in almost every sector. Automotive industry has significant importance in terms of economy and employment when considered its sub-industry and other related sectors. Therefore, it is important to evaluate the adoption level of green manufacturing concept in this sector. Fuzzy multi criteria decision making (FMCDM) methods which handle uncertainty in decision making problems can be effectively used for green performance evaluation of companies. In this study, it is aimed to assess green performance of manufacturers which operate in automotive sector by using a MCDM model based on fuzzy analytic hierarchy process (FAHP) method. This model consists of 5 main criteria which are green design, green energy, green material, green logistics and green management, and 19 sub criteria located under these main criteria. As a result of the study, green energy and low waste criteria were determined as the most important main and sub criteria with weights of 0.268 and 0.1026 respectively. The proposed model can be used as an effective tool for companies operating in the automotive industry to measure and to follow their green performance and to select their suppliers.

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“…Goyal et al [28] recommended a tuning model for configuring reconfigurable manufacturing system. Karatas et al [29] assessed energy management performance of Turkey by an integrated model. Gungor and Kocamis [30] evaluated financial performance of UK soccer clubs.…”

Section: Topsismentioning

confidence: 99%

An Integrated Solution Approach for Flow Shop Scheduling

Karacan

Şenvar

et al. 2021

Teh. vjesn.

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This study seeks to integrate Random Key Genetic Algorithm (RKGA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to compute makespan and solve the Flow Shop Scheduling Problem (FSSP). FSSP is considered as a Multi Criteria Decision Making Problem (MCDM) by setting machines as criteria and jobs as alternatives. RKGA is employed to determine the best weights for the criteria that directly affect the robustness of the solution. The proposed methodology is presented with illustrative example and applied to benchmark problems. The solutions are compared to well-known construction heuristics. The proposed methodology provides the best or reasonable solutions in acceptable computational times.

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Assessment of Turkey's energy management performance via a hybrid multi-criteria decision-making methodology

Cited by 29 publications

References 63 publications

Analyzing Renewable Energy Sources of a Developing Country for Sustainable Development: An Integrated Fuzzy Based-Decision Methodology

Analyzing Renewable Energy Sources of a Developing Country for Sustainable Development: An Integrated Fuzzy Based-Decision Methodology

Otomotiv Endüstrisi için Bulanık Tabanlı Bir Yeşil Performans Değerlendirme Modeli

An Integrated Solution Approach for Flow Shop Scheduling

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