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    3PL Service Provider Selection with a Goal Programming Model Supported with Multicriteria Decision Making Approaches
    (GAZI UNIV, 2020) Ozcan, Evrencan; Ahiskali, Merve
    In this study, third-party logistics (3PL) service provider selection problem is handled for a foreign trade company that exports the products with high quality level obtained by outsourcing, and who has problems regarding both cost, delivery quality and delivery time. In this direction, 7 criteria are determined for effective evaluation of the performance of the 5 logistics service providers the company is working for and the determination of the most suitable 3PL service provider according to the property of the orders (quantity, mode of conveyance, transportation channel, etc.). The priority levels of service providers are calculated by using these criteria in the combination of Analytic Hierarchy Process (AHP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Then, a goal programming (GP) model that answers the question of which service provider to choose for which order, considering these priority values and the 12 system constraints and 5 objectives that the company encountered in real life is proposed. This model is the first one proposed in the literature for the selection of 3PL service providers for multimodal international transport with consistent results. The model is solved for the current 10 orders using the last 1-year data of the company and the most appropriate 3PL service provider combination is obtained. As a result of the solution of the problem with this methodology, an improvement is achieved about 7% for the rate of delivery on time, 33% for bid - bill consistency rate, and 29% for the problematic delivery rate.
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    A Hierarchical Decision Model Proposal for Maintenance Strategy Selection in the Hydroelectric Power Plants
    (Gazi Univ, 2022) Yazici, Emre; Ozcan, Evrencan; Alakas, Haci Mehmet; Eren, Tamer
    Today, the energy demand is increasing day by day. Facilities that provide energy supply develop policies and practices that will continuously respond to this increasing demand. One of the factors that are effective in ensuring continuity in energy is to determine the maintenance strategies of the power plants where energy is produced in a way that does not interrupt the supply. In this study, it is aimed to find the most critical electrical equipment in a hydroelectric power plant and to choose the maintenance strategy for this equipment. This study consists of two stages. First, the most critical electrical equipment was identified. The Pythagorean Fuzzy Analytical Hierarchy Process (PFAHP) was used to determine the weights of the criteria used for ranking the equipment. For ranking the alternatives, the PBAHP method and the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method were integrated. The most appropriate maintenance strategy for generator equipment, which is determined as the most critical electrical equipment, has been determined as revision maintenance.
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    A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants
    (Gazi Univ, 2021) Ozcan, Evrencan; Gur, Seyda; Eren, Tamer
    The main goal of power plants is to generate the electricity in sustainability perspective consisting of the principles of environmental awareness, reliability, efficiency, economy and uninterruptedness. Complying with the operational directives and maintenance are twin pillars for achieving this comprehensive goal. Within this scope, this study handles the maintenance strategy selection problem which is the first step of the effective maintenance management for one of the most important equipment groups among thousands of equipment in one of the large-scale hydroelectric power plants which have great importance for Turkey energy mix with approximately a fifth share in the total generation. So as to determine the most critical equipment group AHP-TOPSIS combination is used. For the selected equipment group, the most appropriate of all applicable 4 maintenance strategies are determined via PROMETHEE, which has been limited used for the maintenance strategy selection problem in the literature despite its advantages. As a result of this study which is the first in the literature with its method configuration and its application in hydroelectric power plants, a 1-year observation is conducted to confirm the proposed approach, and a 100% improvement is achieved in the unit shutdowns resulting from the selected equipment.
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    A novel approach to optimize the maintenance strategies: a case in the hydroelectric power plant
    (Polish Maintenance Soc, 2021) Ozcan, Evrencan; Yumusak, Rabia; Eren, Tamer
    Countries need to develop sustainable energy policies based on the principles of environmental sensitivity, reliability, efficiency, economy and uninterrupted service and to maintain their energy supply in order to increase their global competitiveness. In addition to this impact of sustainable energy supply on the global world, maintenance processes in power plants require high costs due to allocated time, materials and labor, and generation loss. Thus, the maintenance needs to be managed within a system. This makes analytical and feasible maintenance planning a necessity in power plants. In this context, this study focuses on maintenance strategy optimization which is the first phase of maintenance planning for one of the large-scale hydroelectric power plants with a direct effect on Turkey's energy supply security with its one fifth share in total generation. In this study, a new model is proposed for the maintenance strategy optimization problem considering the multi-objective and multi-criteria structure of hydroelectric power plants with hundreds of complex equipment and the direct effect of these equipment on uninterrupted and cost-effective electricity generation. In the model, two multi-criteria decision-making methods, AHP and COPRAS methods, are integrated with integer programming method and optimal maintenance strategies are obtained for 571 equipment.
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    A novel approach towards evaluation of joint technology performances of battery energy storage system in a fuzzy environment
    (Elsevier, 2021) Bulut, Merve; Ozcan, Evrencan
    The joint technological features of battery energy storage systems (BESSs), which are a strategic reserve resource with different operating systems, make it possible for these technologies to be comparable with each other. However, technology needs to be evaluated with stakeholders in the energy system to eliminate some engineering and feasibility concerns, to be included in energy storage policies, and to be utilizable. This aim has involved a high level of complexity and uncertainty, as well as many qualitative and quantitative criteria in both technology and stakeholder assessment. Therefore, in the study, Pythagorean Fuzzy (PF) sets, which offer the decision-maker the advantage of a wide evaluation scale, were used with AHP-TOPSIS combination, which has proven effective in many different applications in the literature. The first use of this methodology for joint technology performance evaluation of BESSs will be a visionary contribution to the literature. In the case study, 5 different BESSs (Lead-acid, Lithium-ion, Vanadium redox flow battery, Sodium nickel chloride, Sodium-sulfur) alternatives have been evaluated with the joint technological criteria of these alternatives. The results show that the most important criteria in battery performance are lifetime calendric, energy rating/discharge time, and life cycle criteria, respectively. Another conclusion of the case study is that while the rapidly developing Lithium-ion battery takes the first place in future projections, it takes second place in Lead-acid batteries, which are mature technology.
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    Advanced forecast models for the climate and energy crisis: The case of the California independent system operator
    (Pergamon-Elsevier Science Ltd, 2025) Bulut, Merve; Aydilek, Huseyin; Erten, Mustafa Yasin; Ozcan, Evrencan
    Climate change across the globe, especially extreme temperature events, is increasing pressures on energy systems. The extraordinary situation that California and the West faced in late August and early September 2022, when record temperatures led to a spike in electricity demand, provided an important backdrop for the resilience and sustainability of clean energy technologies. The electricity market managed by the California Independent System Operator is considered in this study to examine the potential impacts on electricity demand spikes and system resilience. The methodology of the research involves analyzing the system operator's responses to electricity demand using advanced deep learning algorithms, convolutional neural network - long-short term memory and attention mechanism models. 1, 3 and 7-days forecasts of electricity demand were made using models in the day ahead market. In 1-day forecasts, while the former models have a mean absolute percentage error value of 12.40%, the latter model has a lower error rate of 10.36%. Overall findings obtained from various scenarios show that the long-short term memory - attention mechanism can more effectively understand complex patterns in energy demand and has the potential to increase system stability against such extreme weather events. The advanced horizon of the study offers an important perspective on how clean energy technologies, especially battery energy storage systems, can provide solutions to today's priority problems such as climate change and extreme temperature.
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    An artificial neural network model for maintenance planning of metro trains
    (Gazi Univ, 2021) Gencer, M. Abdullah; Yumusak, Rabia; Ozcan, Evrencan; Eren, Tamer
    In urban transportation, trains have an increasingly important place due to the increase in the number of passengers. Meeting the number of passengers is directly related to the number of trains operated on a line. Thus, the frequency of operation of trains affects the level of wear of the equipment. This makes train maintenance more important. Equipment faults are the basis for train maintenance. However, the fault times of the equipment which are unknown causes uncertainty in the maintenance activities and plans. This uncertainty results from many factors that affect the faults of the train. If historical maintenance data, fault data, and factors affecting the faults are known, effective use of resources (time, cost and personnel, etc.) is provided and uncertainty is eliminated. In this study, firstly, maintenance data in Ankara Metro between 2017 and 2018 is examined and the factors affecting equipment faults are evaluated with expert opinion. Artificial Neural Network (ANN) model is created with the data set and this data set along with the factors affecting each the equipment fault according to the type of equipment. In the ANN model, 5 factors (Equipment Type, Preventive Maintenance Frequency, Material Quality, Life Cycle, Line Status) affecting the faults of the equipment is determined as inputs and the number of failures as outputs. The mean absolute percent error (MAPE) value is found as 11%, and the mean square error value (MSE) is 0.0028229 in the training and test stages of ANN. Then, the frequency of fault is found according to the equipment fault and a 10-week maintenance planning is applied. The results are compared with current maintenance planning. As a result of the applied maintenance planning, the average number of faults of the trains decreases by 27%, uninterrupted service rate increases by 40% and heavy maintenance errors are also prevented. Fault removal times resulted in a 10% improvement. The results showed that ANN models could be used effectively in fault prediction and maintenance planning with rail system multiple types of equipment. In the literature, there is no study that implements maintenance planning with an ANN model where all train equipments and factors affecting the failure are evaluated together. This study is the first in the field of rail systems maintenance in the literature and will be a reference for future studies.
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    An integrated model for evaluating the risk factors of crypto-currencies under fuzzy environment
    (Pergamon-Elsevier Science Ltd, 2024) Bulut, Merve; Uyar, Mehmet Erkin; Ozcan, Evrencan
    While blockchain technology and cryptocurrencies offer numerous advantages and innovations, it is essential to be aware that their implementation processes are fraught with a myriad of risk factors. A study in which risks in cryptocurrencies are evaluated using quantitative data is an important need for investors and academics. As far as it is known from the literature, although blockchain technology is frequently used in different fields, there is no study examining the risks in cryptocurrencies with fuzzy set theory. Unlike the common return and security focused studies in the literature, a comprehensive risk factor determination has been made by evaluating a total of 21 criteria that directly and indirectly affect this virtual currency. Within the study, investors have been provided with insights into the alternatives relevant to the risks under determined through the utilization of an alternative set of considerable magnitude, uncommonly encountered in the existing literature. Considering the complexity and uncertainty of the problem, an Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution method integrated with Spherical fuzzy sets have been used. The most preferred cryptocurrencies have been evaluated according to a set of criteria ranging from their financial structures to their environmental impacts. Ethereum, which stands out with its blockchain structure, has been the best choice. Tether, designed to provide a stable price point, and Dogecoin, designed as a payment system, appeared to be the worst ones.
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    An Artificial Neural Network Model Supported With Multi Criteria Decision Making Approaches For Maintenance Planning In Hydroelectrıc Power Plants
    (POLISH MAINTENANCE SOC, 2020) Ozcan, Evrencan; Danisan, Tugba; Yumusak, Rabia; Eren, Tamer
    Power plants are the large-scale production facilities with the main purpose of realizing uninterrupted, reliable, efficient, economic and environmentally friendly energy generation. Maintenance is one of the critical factors in achieving these comprehensive goals, which are called as sustainable energy supply. The maintenance processes carried out in order to ensure sustainable energy supply in the power plants should be managed due to the costs arising from time requirement, the use of material and labor, and the loss of generation. In this respect, it is critical that the fault dates are forecasted, and maintenance is performed without failure in power plants consisting of thousands of equipment. In this context in this study, the maintenance planning problem for equipment with high criticality level is handled in one of the large-scale hydroelectric power plants that meet the quintile of Turkey's energy demand as of the end of 2018. In the first stage, the evaluation criteria determined by the power plant experts are weighted by the Analytical Hierarchy Process (AHP), which is an accepted method in the literature, in order to determine the criticality levels of the equipment in terms of power plant at the next stage. In order to obtain the final priority ranking of the equipment in terms of power plant within the scope of these weights, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used because of its advantages compared to other outranking algorithms. As a result of this solution, for the 14 main equipment groups with the highest criticality level determined on the basis of the power plant, periods between two breakdowns are estimated, and maintenance planning is performed based on these periods. In the estimation phase, an artificial neural network (ANN) model has been established by using 11-years fault data for selected equipment groups and the probable fault dates are estimated by considering a production facility as a system without considering the sector for the first time in the literature. With the plan including the maintenance activities that will be carried out before the determined breakdown dates, increasing the generation efficiency, extending the economic life of the power plant, minimizing the generation costs, maximizing the plant availability rate and maximizing profit are aimed. The maintenance plan is implemented for 2 years in the power plant and the unit shutdowns resulting from the selected equipment groups are not met and the mentioned goals are reached.
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    Bakım ekiplerinin en kısa yoldan santrallara ulaşımı: hidroelektrik santral örneği
    (2021) Danışman, Tuğba; Ozcan, Evrencan; Eren, Tamer
    Elektrik santralları bir ülkenin enerji arzının karşılanmasına hizmet eden önemli tesislerdir. Elektrik enerji talebinin sürekli olması nedeniyle elektrik üretimininde kesintisiz olması gerekmektedir. Bu durum santralların uzun yıllar çalışmasından kaynaklı yıpranmasına yol açmaktadır. Üretiminsürdürülebilirliğinin sağlanması için santrallara bazı bakımların yapılması gerekmektedir. Bu nedenle santrallardaki arızaların giderilmesi ve bakımlarınyapılması için zaman önemli bir kısıttır. En kısa zamanda bakımlara başlanması sürdürülebilirlik noktasında önem arz etmektedir. Santraldaki mekanik,elektriksel ve elektronik tüm ekipmanların bakımı, uzman bakım ekipleri tarafından yapılmaktadır. Bu çalışmada Türkiye’deki elektrik enerjisi talebininyaklaşık %31,9’unu karşılayan Hidroelektrik Santrallar (HES) için uygulama yapılmıştır. Çalışmada bakım için görevlendirilen üç ekibin santrallara en kısayoldan ulaşması problemi ele alınmıştır. Türkiye’deki HES’ler arasında yıllık üretim miktarı yüksek olan on iki HES için çalışma yapılmıştır. Santrallardakibakımlarda görev alabilecek ekipler her santralda bulunmamaktadır. Çalışmaya dahil edilen on iki HES için bakımları yapabilecek sadece üç ekipbulunmaktadır. Bu nedenle bu üç ekibin santrallara en kısa yoldan ulaşmaları amaçlanmıştır. Problem çözümünde Floyd-Warshall algoritması kullanılmıştır.C tabanlı bir kod yardımı ile elde edilen çözümler sonucunda bakım ekiplerinin santrallara ulaşımında optimal sonuç veren en kısa yollar bulunmuştur.
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    Decision making for promising quinoline-based anticancer agents through combined methodology
    (WILEY, 2020) Ozcan, Evrencan; Okten, Salih; Eren, Tamer
    During the development of effective drugs for the treatment of cancer, one of the most important tasks is to identify effective drug candidates having maximum antiproliferation and minimum side effects. This paper considers the problem of selecting the most promising anticancer agents, showing inhibition at low IC50 concentration and low releasing lactate dehydrogenase percentage (cytotoxicity). Recently, we prepared quinoline analogs bearing different functional groups and determined their anticancer potential against the HeLa, C6, and HT29 cancer cell lines using different anticancer assays. Experimentally, seven quinoline derivatives consisting of different substituents were determined as promising anticancer agents. We propose a multicriteria recommendation method to identify the most promising anticancer agents against all tested cell lines with an accurate prediction algorithm according to the available input data. A multicriteria decision-making methodology (MCDM) was used for the solution of the relevant problem in this study. Both the experimental results and MCDM method indicated that 5,7-dibromo-8-hydroxyquinoline (2) and 6,8-dibromo-1,2,3,4-tetrahydroquinoline (6) are the most promising anticancer agents against the HeLa, HT29, and C6 cell lines.
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    Deprem Sonrası Mobil Hizmet Tesisi Seçim Problemi için Çok Kriterli Bir Karar Modeli Önerisi
    (2020) Tezcan, Burcu; Özcan, Nermin Avşar; Ozcan, Evrencan; Eren, Tamer
    Afetler meydana geldiği bölgede büyük zararlar vermekte ve toplumsal yaşamı kesintiye uğratmaktadır. Afet öncesinde zararların önlenmesi için alınması gereken tedbirler olduğu gibi sonrasında da afete maruz kalan bölgede kişilerin sağlık, barınma, beslenme, temizlik gibi ihtiyaçları karşılanmalıdır. Deprem gibi yüksek zararlara yol açan ve birçok alanı kullanılamaz hale getiren afetlerde kişilerin ihtiyaçlarının sağlanması için yeni tesislerin kurulması gerekmektedir. Bu aşamada, olası bir deprem öncesinde söz konusu tesislerin yerlerinin analitik bir temelle uygun olarak belirlenmesi, deprem sonrasında depremzedelere hizmetin etkin bir şekilde ulaşmasını sağlayacaktır. Kırıkkale, deprem üretme potansiyeli yüksek fay zonlarına mesafesi nedeniyle deprem tehlikesi yüksek olan bir şehirdir. Ayrıca, Türkiye’nin en önemli ve stratejik sanayi kuruluşlarının üretim tesislerini sınırları içinde bulundurmaktadır. Bunlara ek olarak, Ankara'ya en yakın il olan Kırıkkale, 46 ilin kesiştiği noktada yer almaktadır ve Kırıkkale-Ankara arasında kritik ve büyük sanayi tesisleri bulunmaktadır. Bu gerçekler, söz konusu yerlerde bir felaket için Kırıkkale'de kurulacak mobil hizmet tesislerini daha da önemli hale getirmektedir. Bu kapsamda bu çalışmada, literatürde ilk kez Kırıkkale ilinde mobil hizmet tesisi seçim problemi için çok kriterli bir karar modeli önerilmiştir.
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    Determination of Effective Criteria for Mobile Application Selection and Sample Application
    (Istanbul Univ, 2020) Uslu, Buse; Gur, Seyda; Eren, Tamer; Ozcan, Evrencan
    Today everyone has specially coded and designed software for mobile phones or tablets. The 2017 data from Turkish Statistical Institute (TURKSTAT) show that there are about 78 million mobile phone users and of these the number of internet subscribers selection according to the literature review and expert opinions are language, price, performance, memory usage, user interpretation and speed. The criteria were evaluated by five officials and compared with AHP (Analytical Hierarchy Process) method to determine the significance of the criteria. Thereafter, five mobile application projects were determined and the alternatives were made by applying AHP, TOPSIS and PROMETHEE methods.
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    Dijkstra Algoritması Kullanılarak İpekYolu Koridorları Arasında En KısaUlaştırma Güzergâhının Belirlenmesi
    (2021) Özdemir, Sezgin; Sacar, Ömer; Ozcan, Evrencan
    Çin,çok taraflı ulaştırma politikaları ve 21. yy.İpekYolunu oluşturma hedefi kapsamında 2013 yılında tarihi bir adım atmıştır. “Kuşak ve Yol” sloganı ile Pekin’ den Londra’ ya ulaşan yeni bir ticaret yolunun projesini açıklamış ve güzergâh ülkelerine iş birliğiçağrısına bulunmuştur. Modern İpek Yolu olarak da adlandırılan bu proje; kara, deniz ve demiryolu taşımacılığının kullanılarak Çinilegüzergâhtaki 65’den fazla ülkeyi birbirine bağlanmayı, bu ülkelerde dengeli ve sürdürülebilir ekonomik kalkınmaları hedeflemektedir. Türkiye coğrafi ve jeopolitik konumusayesinde en önemli güzergâh ülkelerinden birisi olarak bu iş birliğindenen fazla beklentisi olan ülke durumundadır. Dolayısıyla Türkiye;demiryolu, karayolu, tüp geçitler ve boğaz köprüleri başta olmak üzere birçok önemli yatırıma imza atmıştır. Literatürde sosyal bilimler alanlarında İpekYolu ile ilgili birçok çalışma mevcuttur. Fakat bu çalışmadakonuya mühendislik uygulamaları yaklaşımıyla,tüm sosyal ve politik koşullardan bağımsız olarak optimal bir sonuç elde etme amacı güdülmüştür. Bu amaçla İpekyolu Koridorlarında Pekin’den Londra’ya ulaşan demiryolu ağı için toplam 26düğümden oluşan bir graf oluşturulmuşve en kısa yolun hesaplanması için Dijkstra algoritması Python programlama dilinde kodlanarak çözülmüştür.Modern İpek Yolu veya Orta Koridorolarak adlandırılan güzergâhın Pekin-Londra arası en kısa demiryolu güzergâhı olduğu sonucuna ulaşılmıştır
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    En Kısa Yol Optimizasyonlarında Floyd-Warshall Algoritması: Lojistik Merkezler Örneği
    (2023) Keskin, Bekir; Ozcan, Evrencan
    Lojistik merkezler taşımacılık, depolama, elleçleme, dağıtım, gümrükleme, ayrıştırma, ithalat, ihracat ve transit işlemler, sigorta ve bankacılık, altyapı hizmetleri, danışmanlık ve üretim vb. faaliyetlerin birbiriyle uyumlu bir şekilde yürütülmesine ve olası taşıma yöntemlerinin bir arada sunulmasına hizmet eden önemli tesislerdir. Yük talebinin sürekli olması nedeniyle yük taşımacılığının da kesintisiz, en kısa yoldan, yakıt tüketimi ve taşıma süresi açısından da optimal bir şekilde gerçekleştirilmesi gerekmektedir. Bu çalışmada yük trenlerinin lojistik merkezlere en kısa yoldan ulaşması problemi ele alınmıştır. Literatürde lojistik köylerle ilgili yazın taraması yapıldığında; lojistik merkezlerin, lojistik sektörüne yapmış olduğu katkılar incelenmiş, güçlü ve zayıf yönleri ortaya konmaya çalışılmış, etkin ve verimli çalışması hakkında önerilerle ilgili çalışmalar gözlemlenmiştir. Fakat bu çalışmada; konuya mühendislik uygulamaları yaklaşımıyla, ülke genelinde faaliyet gösteren on iki lojistik merkezin yanı sıra yapım ve ihale aşamasında yer alan yedi adet lojistik merkez de çalışma kapsamına dâhil edilerek, lojistik merkezler arasında güzergâh seçimi için en uygun sonuç elde etme amacı güdülmüştür. En kısa yol problemlerinin uygulama alanı genellikle bir şebekede/ağda yer alan noktalar arasında en kısa mesafenin belirlenmesi olup, çalışmada şebekedeki herhangi iki düğüm arasındaki en kısa yolun belirlemesi açısından Floyd-Warshall Algoritması tercih edilmiştir. Bu amaçla ulusal demiryolu ağı için toplam 33 düğümden oluşan bir çizge oluşturulmuş ve en kısa yolun hesaplanması için Floyd-Warshall algoritması Python programlama dilinde kodlanarak çözülmüştür ve toplam on dokuz adet lojistik merkez arasında en kısa yol/yollar tespit edilmiştir.
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    Evaluation of the Difficulties in the Internet of Things (IoT) with Multi-Criteria Decision-Making
    (Mdpi, 2019) Uslu, Buse; Eren, Tamer; Gur, Seyda; Ozcan, Evrencan
    The rapid development of technology has increased the desire of all to be on the Internet. The discovery that objects born of the Internet communicate with each other without external factors revealed, with the fourth industrial revolution, the concept of the Internet of Things (IoT). The communication of objects with each other means minimum labor and minimum cost for enterprises. Enterprises that want to transition to the Internet of Things face many difficulties. Identifying and correcting these difficulties can lead to both lost time and high cost. In this study, we investigated the difficulties encountered in the Internet of Things. As a result of the study, the degree of importance of the factors causing these difficulties was determined by multi-criteria decision-making methods and was presented to the enterprises. The main criteria, and the sub-criteria related to these main criteria, were determined. The main purpose of the enterprises transitioning to Industry 4.0 is the communication of things with each other. In this study, we aimed to determine which criteria caused difficulties in the transition to Industry 4.0. Then, the degree of importance of the criteria was determined using the analytic hierarchy process (AHP) and analytic network process (ANP) methods, in the multi-criteria decision-making. Through the study, we determined which criteria should be taken into consideration by the enterprises that want to transition to the Internet of Things. In this way, enterprises will be able to accelerate that transition by minimizing time and monetary loss.
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    Evaluation of the hybrid renewable energy sources using sustainability index under uncertainty
    (Elsevier, 2021) Yurek, Yagmur Torul; Bulut, Merve; Ozyoruk, Bahar; Ozcan, Evrencan
    Asa result of continuous growth in population, efforts to meet increasing energy demand in a balanced way in the future as it is today, has led to the emergence of the sustainability concept. Sustainability is mainly considered with technical, economic, environmental and social aspects, hence the most effective instruments to ensure sustainability are renewable energy technologies which are interchangeably used for sustainability. Renewable energy problems regarding sustainability have inherently conflicting goals with a high degree of ambiguity and complexity. To address these problems, multi-criteria decision making (MCDM) approach serve best. Therefore, in this study, a MCDM approach integrating Pythagorean fuzzy sets (PFSs) in AHP-TOPSIS method combination was used to calculate the sustainability index and for ranking renewable energy technologies, hybrids and battery energy storage systems (BESSs) in Turkey. The sustainability index was handled in three main aspects, i.e., uninterrupted supply, economic supply and environmentally friendly supply. The results pointed out that hydro + solar and wind + solar hybrid alternatives have the highest sustainability index value while geothermal and biomass rank as the lowest two alternatives energy technologies. (C) 2021 Elsevier Ltd. All rights reserved.
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    Goal Programming Approach For The Radiology Technician Scheduling Problem
    (Yildiz Technical Univ, 2019) Ozcan, Evrencan; Danisan, Tugba; Yumusak, Rabia; Gur, Seyda; Eren, Tamer
    Population growth is led to an increase in demand in the health sector. Health services need to be met at the maximum level in the face of increasing demand. The number of patients per each health personnel in Turkey is too much. Considering this situation, it is seen that ensuring patient satisfaction is directly proportional to the satisfaction of the personnel. For this reason, some studies such as the positioning of polyclinics and hospitals encountered in health services, capacity planning and demand estimations, as well as the studies about the creation of study schedules of health personnel are also gained importance. In this study, it is aimed to provide the personnel satisfaction as much as possible. The Law No. 3153 on Radiology, Radionomy and Electrical Therapy and Other Physiotherapy Institutions published by the Ministry of Health of the Republic of Turkey, dated 19/4/1937, as well as the requirements of the Annex-1 of 21/1/2010, is considered. The scheduling problem for eight radiology technicians working in a private hospital in Ankara is discussed. A mathematical model is proposed using the goal programming method in order to assign the technicians to the four shifts as equally as possible. According to the researches, this is the first study which has the feature of radiology technicians and by considering government and hospital conditions as well as with staff requests, by application area.
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    Hidroelektrik santrallarda bakım çizelgeleme için hibrid bir model önerisi
    (2020) Ozcan, Evrencan; Danışman, Tuğba; Eren, Tamer
    Bakım, endüstriyel işletmelerde üretim, personel ve malzeme ile eş zamanlı yönetilmesi gereken önemli bir prosestir. Bu önemli prosesin kritik aşamalarının başında bakım planlaması gelmektedir. Bakım planlaması için gerekli olan iki aşama bulunmaktadır. İlk aşama bakım stratejilerinin belirlenmesi ve ikinci aşama ise bakım çizelgelerinin oluşturulmasıdır. Bu çalışma, bakım planlamasının ilk adımını oluşturan bakım strateji seçiminin gerçekleştirildiği bir çalışmanın devamı olarak bakım çizelgelemesi için yapılmıştır. Bakım strateji seçimi için gerçekleştirilen ilk adımdaki çalışmada [5], Türkiye’deki büyük ölçekli bir hidroelektrik santralda yer alan 1330 elektriksel ekipman incelenmiş ve santral açısından kritiklik seviyesi belirlenmiştir. Çalışma sonucunda bir zaman çizelgesi doğrultusunda gerçekleştirilebilecek olan, periyodik bakım stratejisinin uygulanabileceği kritik elektriksel 7 ana ekipman grubu belirlenmiştir. Elde edilen bu sonuçlar bakım planlamasındaki bakım çizelgeleme aşamasını oluşturan bu çalışmada kullanılmıştır ve periyodik bakım stratejisinin uygulanabileceği bu kritik elektriksel 7 ana ekipman grubu için bakım çizelgesi oluşturulmuştur. Bakım çizelgeleme için yapılan bu çalışmanın ilk aşamasında santralın bir yıllık üretim tahmini Yapay Sinir Ağı (YSA) yöntemi ile gerçekleştirilmiş ve bu tahmin sonucunda elde edilen verilerden çalışma-bakım süreleri hesaplanmıştır. Tutarlı tahmin değerlerinin santralın bakım planlama gerçek ve gerekliliklerini yansıtan 0-1 Tam sayılı Programlama (TP) modelinde kullanılmasıyla, beş farklı periyodik bakım türü çizelgelenmiş ve santral işletme ve bakım gerçekleri ile tutarlı optimal bir bakım planı elde edilmiştir.
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    Öğe
    How to build a state-of-the-art battery energy storage market? Challenges, opportunities, and future directions
    (Elsevier, 2024) Bulut, Merve; Ozcan, Evrencan
    The leading role of the recent developments in critical energy storage technologies that will ensure universal energy access in a balanced and reliable way belongs to battery energy storage systems (BESSs), which are a robust stakeholder. The fact that these are regulated instruments in electricity markets, due to their technical nature when equipped with solid policies, can serve not only the purpose of carbon neutrality and net zero but also restrain the problems of warming and climate change. This study, which is an answer to the questions of how modern policies affect the markets and how the markets shape the policies, explores the strategic balance of BESSs in the role of price taker/price maker when it comes to market effect. Strategic balance encompasses not only the commercial maneuvers of policymakers within the liberalized electricity market, but also the decay of electrochemical accumulations throughout their practical life cycles, considering the utilization of industrial symbiosis practices to promote a circular economy for the disposal of end-of-life (EoL) electrochemical stacks. In this respect, this study, which establishes the policy-market-symbiosis triangle for BESSs, is the first to examine this perspective in the literature to the best of our knowledge. Each corner of the triangle systematically considers the role of policies, market dynamics, and symbiotic relationships in directing the deployment and use of these modern systems towards a common goal.