Yücekaya, Ahmet Deniz
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A. Yücekaya
YÜCEKAYA, AHMET DENIZ
Yücekaya, A.
Yucekaya A.
Yücekaya, Ahmet Deniz
Yücekaya,A.D.
Ahmet Deniz, Yucekaya
Ahmet Deniz YÜCEKAYA
Yücekaya, A. D.
AHMET DENIZ YÜCEKAYA
Yucekaya,Ahmet Deniz
A. D. Yücekaya
Yucekaya,A.D.
Ahmet Deniz Yücekaya
Yucekaya, Ahmet Deniz
YÜCEKAYA, Ahmet Deniz
Y.,Ahmet Deniz
Yücekaya, AHMET DENIZ
Y., Ahmet Deniz
Yücekaya, Ahmet Çelebi
Yücekaya, Ahmet Deniz
Yucekaya, Ahmet
Yücekaya, Ahmet
YÜCEKAYA, AHMET DENIZ
Yücekaya, A.
Yucekaya A.
Yücekaya, Ahmet Deniz
Yücekaya,A.D.
Ahmet Deniz, Yucekaya
Ahmet Deniz YÜCEKAYA
Yücekaya, A. D.
AHMET DENIZ YÜCEKAYA
Yucekaya,Ahmet Deniz
A. D. Yücekaya
Yucekaya,A.D.
Ahmet Deniz Yücekaya
Yucekaya, Ahmet Deniz
YÜCEKAYA, Ahmet Deniz
Y.,Ahmet Deniz
Yücekaya, AHMET DENIZ
Y., Ahmet Deniz
Yücekaya, Ahmet Çelebi
Yücekaya, Ahmet Deniz
Yucekaya, Ahmet
Yücekaya, Ahmet
Job Title
Prof. Dr.
Email Address
Main Affiliation
Industrial Engineering
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
4
QUALITY EDUCATION
0
Research Products
6
CLEAN WATER AND SANITATION
6
Research Products
10
REDUCED INEQUALITIES
0
Research Products
13
CLIMATE ACTION
2
Research Products
14
LIFE BELOW WATER
0
Research Products
2
ZERO HUNGER
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
1
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
3
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
5
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
1
NO POVERTY
0
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
8
Research Products
15
LIFE ON LAND
0
Research Products
3
GOOD HEALTH AND WELL-BEING
1
Research Products
7
AFFORDABLE AND CLEAN ENERGY
7
Research Products
5
GENDER EQUALITY
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
Documents
34
Citations
539
h-index
13
Documents
22
Citations
423
Scholarly Output
48
Articles
30
Views / Downloads
10/0
Supervised MSc Theses
9
Supervised PhD Theses
2
WoS Citation Count
359
Scopus Citation Count
493
WoS h-index
11
Scopus h-index
13
Patents
0
Projects
0
WoS Citations per Publication
7.48
Scopus Citations per Publication
10.27
Open Access Source
27
Supervised Theses
11
| Journal | Count |
|---|---|
| International Journal of Energy Economics and Policy | 7 |
| Journal of Hydrologic Engineering | 4 |
| Energy Sources, Part B: Economics, Planning, and Policy | 3 |
| Renewable and Sustainable Energy Reviews | 2 |
| Energy Strategy Reviews | 2 |
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48 results
Scholarly Output Search Results
Now showing 1 - 10 of 48
Article Citation - WoS: 11Citation - Scopus: 17A Fuzzy Anp-Based Gra Approach To Evaluate Erp Packages(IGI Global, 2019) Ayağ, Zeki; Yücekaya, AhmetOne of the major problems that most companies face with during the implementation of an ERP system is to determine the best satisfying ERP software based on their needs and expectations. Because an improperly selected ERP software might lead to time loss and increased costs and in the long run a loss of market share. Therefore the ERP evaluation process for companies becomes to a vital point. On the other hand evaluating ERP software alternatives under a set of criteria leads us to a multiple-criteria decision making (MCDM) problem and needs to use proper MCDM methods. In the current literature a number of the MCDM methods have been proposed to solve these kinds of problems both of which are the analytic network process (ANP) of Saaty and grey relational analysis (GRA) which has been widely used in solving MCDM selection problems in various fields. Moreover in this article the authors used the fuzzy extension of the ANP method to reflect the uncertainty and ambiguity of decision maker(s) into problem in order to reach more reliable solution. As the fuzzy ANP method was used to calculate the priority weights of the evaluation criteria the GRA method with fuzzy interval-values was employed to rank a set of the possible ERP software alternatives. The proposed approach was also validated in a case study to show its applicability to potential readers and practitioners. Copyright © 2019 IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.Article Citation - Scopus: 14Nutrient Dynamics in Flooded Wetlands. Ii: Model Application(2013) Kalin,L.; Hantush,M.M.; Isik,S.; Yucekaya,A.; Jordan,T.In this paper, the authors applied and evaluated the wetland nutrient model that was described in Paper I. Hydrologic and water quality data from a small restored wetland located on Kent Island,Maryland, which is part of the Delmarva Peninsula on the eastern shores of the Chesapeake Bay, was used for this purpose. The model was assessed through various methods against the observed data in simulating nitrogen (N), phosphorus (P), and total suspended sediment (TSS) dynamics. Time series plots of observed and simulated concentrations and loads generally compared well; better performance was demonstrated with dissolved forms of nitrogen, i.e., ammonia and nitrate. Through qualitative and quantitative sensitivity analysis, dominant processes in the study wetland were scrutinized. Nitrification, plant uptake, and mineralization were the most important processes affecting ammonia. Denitrification in the sediment layer and diffusion to bottom sediments were identified as key processes for nitrate. Settling and resuspension were the most important processes for particulate matter (organic N, sediment) and sediment-bound phosphate (inorganic P). Order of parameter sensitivities and dominant processes exhibited seasonality. Uncertainty bands created from Monte Carlo simulations showed that parameter uncertainty is relatively small; however, uncertainty in the wetland inflow rates and loading concentrations have much more bearing on model predictive uncertainty. N, P, and TSS mass balance analysis showed that the wetland removed approximately 23, 33, and 46%, respectively, of the incoming load (runoff + atmospheric deposition) over the two-year period, with more removal in year 1 (34, 43, and 55%, respectively), which had a long stretch of a dry period. The developed model can be employed for exploring wetland response to various climatic and input conditions, and for deeper understanding of key processes in wetlands. © 2013 American Society of Civil Engineers.Conference Object Citation - WoS: 2Citation - Scopus: 3The Implementation of Smart Contract via Blockchain Technology in Supply Chain Management: A Case Study from The Automotive Industry in Turkey(IEEE, 2021) Yuksel, Hasan Basri; Bolat, Serdar; Bozkurt, Hayreddin; Yucekaya, Ahmet; Hekimoglu, MustafaBlockchain Technology, underlined as the most revolutionizing innovation after the internet, is still in the growth phase and waits for the practitioners to enlighten its productivity promises. In the current environment, volatile profits require a more digitalized work experience and competitive advantages to get ahead in such a highly competitive automotive industry and innovative applications that lead to more simplified operation management. Accordingly, this paper aims to present a case study via use cases in which Blockchain has been used and smart contract as the sought-out innovation and its application for the digitized spare parts disposal legal process. Blockchain Technology in the automotive sector is discussed by focusing on the supply management process of an automotive company's processes in Turkey. Blockchain technology is expected to develop and simplify spare parts-related transactions in the automotive industry, which deals with more than 500K stock keeping units per company. Paper presents the current, future, and ideal states of spare parts transactions with Blockchain adoption. The implemented application enables the development of an enterprise-level blockchain platform with hyper-ledger fabric as an open-source. The distributed ledger technology provides a smart contract system between actors of the existed supply chain process. The study aims to show the potential of Blockchain Technology in delivering a high degree of competitive advantage especially for automotive service providers with regards to its features related to providing security, transparency, traceability, cost reduction, more efficient data storage in dense supply based industries.Conference Object A Comparative Application of Machine Learning Approaches To Win-Back Lost Customers(Institute of Electrical and Electronics Engineers Inc., 2023) Yildirim, S.; Yucekaya, A.D.; Hekimoglu, M.; Ozcan, B.Today's consumer is more knowledgeable and conscious than in the past. For this reason, it is quite possible for consumers to leave their service/product providers and start receiving service from another service/product provider. Without a recovery strategy, companies often do not target their lost disloyal customer portfolio correctly and encounter the problem of lost customers. Lost customers can cause loss both in economic terms and in terms of business potential. At the same time, lost customers can also be considered as profits given to rival companies. What if the companies could foresee lost customers who would not want to receive service from them again? Could companies win back their customers? At this point, the article proposes using machine learning methods to recover lost customers for service providers. The customers that are likely to be lost in the future are estimated using the article's past stories of an automotive company's lost customers. The data used is completely real. LGBM, XGBoost, and Random Forest methods were used to estimate lost customers. Finally, the authors select the machine learning with the highest predictive success for customer recovery and discuss why this method might have worked well. © 2023 IEEE.Article Citation - WoS: 12Citation - Scopus: 15Forecasting Models for Daily Natural Gas Consumption Considering Periodic Variations and Demand Segregation(Elsevier Ltd, 2020) Yükseltan, Ergün; Yücekaya, Ahmet; Bilge, Ayşe Hümeyra; Ağca Aktunç, EsraDue to expensive infrastructure and the difficulties in storage, supply conditions of natural gas are different from those of other traditional energy sources like petroleum or coal. To overcome these challenges, supplier countries require take-or-pay agreements for requested natural gas quantities. These contracts have many pre-clauses; even if they are not met due to low/high consumption or other external factors, buyers must completely fulfill them. A similar contract is then imposed on distributors and wholesale consumers. It is, thus, important for all parties to forecast their daily, monthly, and annual natural gas demand to minimize their risk. In this paper, a model consisting of a modulated expansion in Fourier series, supplemented by deviations from comfortable temperatures as a regressor is proposed for the forecast of monthly and weekly consumption over a one-year horizon. This model is supplemented by a day-ahead feedback mechanism for the forecast of daily consumption. The method is applied to the study of natural gas consumption for major residential areas in Turkey, on a yearly, monthly, weekly, and daily basis. It is shown that residential heating dominates winter consumption and masks all other variations. On the other hand, weekend and holiday effects are visible in summer consumption and provide an estimate for residential and industrial use. The advantage of the proposed method is the capability of long term projections, reflecting causality, and providing accurate forecasts even with minimal information.Master Thesis Decarbonization Pathways For Turkish Power System Using The Leap Model Leap Modeli Kullanılarak Türkiye Elektrik Sistemi için Dekarbonizasyon Yolları(Kadir Has Üniversitesi, 2021) Özer, Fatma Ece; Kirkil, Gökhan; Yücekaya, Ahmet DenizThe negative impact of GHG released into the atmosphere on global warming cannot be ignored. Fossil-fueled power plants constitute a large part of Turkey's electricity production, as every country has a growing economy. Therefore, the electricity generation sector accounts for a significant portion of GHG emissions in Turkey. In addition to national bindings such as the Paris Agreement and the Kyoto Protocol, it is known that the Republic of Turkey aims to make not only electricity but also energy production greener in the coming years, in line with its own efforts. For this purpose, there are different modeling studies in the literature. This thesis aims to model Turkey's electricity generation sector in 2017, reveal the current situation, and then analyze how a greener and sustainable energy transformation will be possible with different scenarios and different main factors. In this direction, Turkey's electricity generation sector was modeled using the LEAP tool, then the decarbonization scenarios created within the openENTRANCE project were adapted to Turkey's data, and the numerical results of the scenarios were compared. As a result, it has been revealed that social awareness, adaptation to new technologies, and incentives of decision-makers are all critical factors in this regard.Article Citation - WoS: 24Citation - Scopus: 31Electricity trading for coal-fired power plants in Turkish power market considering uncertainty in spot, derivatives and bilateral contract market(Pergamon-Elsevier Science Ltd, 2022) Yucekaya, AhmetIn deregulated power markets, electricity suppliers have the option to trade in the spot market, derivatives market, and bilateral contract market. The spot market is always available and open to competition, but the variability and risk incurred need to be carefully handled. The suppliers might allocate their capacity in the derivatives and bilateral contract market if these alternatives are more viable. The strike price, bilateral contract price, and spot market prices need to be used to decide the capacity allocation problem considering the generation cost of the supplier. This paper first examines the market design and electricity trading in the Turkish electricity market. Then three problems were proposed for a coal-fired coal unit that aims to allocate its capacity to spot, derivative, and bilateral contract markets to maximize its expected profit. A Monte Carlo method is used for allocated electricity capacities, spot market, strike, and bilateral contract price scenarios. A simulation methodology is then proposed that includes capacities allocated to each market and price scenarios. The best capacity allocation strategy is determined that return the highest expected profits for all market price samples. The model is illustrated for a coal unit in the Turkish electricity market. The results are presented for the case, including 100 spot price samples, 100 capacity scenarios, 3 scenarios for the strike, and bilateral contract prices. The sensitivity analysis for spot price volatility on the profit is also presented with 20% volatility increase. It is shown that allocating the capacity to more than one market can increase the total expected profit for a power supplier and the rate of increase varies depending on the scenario set.Article Citation - Scopus: 31Nutrient Dynamics in Flooded Wetlands. I: Model Development(2013) Hantush,M.M.; Kalin,L.; Isik,S.; Yucekaya,A.Wetlands are rich ecosystems recognized for ameliorating floods, improving water quality, and providing other ecosystem benefits. This part of a two-paper series presents a relatively detailed process-based model for nitrogen and phosphorus retention, cycling, and removal in flooded wetlands. The model captures salient features of nutrient dynamics and accounts for complex interactions among various physical, biogeochemical, and physiological processes. The model simulates oxygen dynamics and the impact of oxidizing and reducing conditions on nitrogen transformation and removal, and approximates phosphorus precipitation and releases into soluble forms under aerobic and anaerobic conditions, respectively. Nitrogen loss pathways of volatilization and denitrification are explicitly accounted for on a physical basis. Processes in surface water and the bottom-active soil layer are described by a system of coupled ordinary differential equations. A finite-difference numerical scheme is implemented to solve the coupled system of ordinary differential equations for various multiphase constituents' concentrations in the water column and wetland soil. The numerical solution algorithm is verified against analytical solutions obtained for simplified transport and fate scenarios. Quantitative global sensitivity analysis revealed consistent model performance with respect to critical parameters and dominant nutrient processes. A hypothetical phosphorus loading scenario shows that the model is capable of capturing the phenomenon of phosphorus precipitation and release under oxic and anoxic conditions, respectively. © 2013 American Society of Civil Engineers.Master Thesis A Decision Support System for Assembly Line Balancing Problem(Kadir Has Üniversitesi, 2015) Ringim, İbrahim Uba; Yücekaya, Ahmet DenizAssembly line balancing problems are generally considered to be complicated in real life. Like most complicated real life assembly line balancing problems obtaining a good solution is much easier than finding an optimal solution especially with big size problems. As a result, many heuristic approaches have been developed to find good optimal solutions to those problems. In this study, we develop a decision support system that solves a deterministic assembly line balancing problem using three heuristic approaches. The objectives considered are: minimizing the number of workstations, maximization of line efficiency and minimization of balance delay. Our aim is using the decision support system created; user can enter any value into the system and obtain 3 different results. The results obtained are feasible enough which shows that the decision support system works and can be able to solve even larger problems if the correct formula is appliedArticle Citation - Scopus: 19Optimization of Wastewater Treatment Systems for Growing Industrial Parks(Elsevier B.V., 2023) Savun-Hekimoğlu, B.; İşler, Z.; Hekimoğlu, M.; Burak, S.; Karlı, D.; Yücekaya, A.; Akpınar, E.Wastewater treatment is one of the crucial functions of industrial parks as wastewater from industrial facilities usually contains toxic compounds that can cause damage to the environment. To control their environmental loads, industrial parks make investment decisions for wastewater treatment plants. For this, they need to consider technical and economic factors as well as future growth projections as substantial construction and operational costs of wastewater treatment plants have to be shared by all companies in an industrial park. In this paper, we consider the long-term capacity planning problem for wastewater treatment facilities of a stochastically growing industrial park. By explicitly modeling randomness in the arrival of new tenants and their random wastewater discharges, our model calculates the future mean and variance of wastewater flow in the industrial park. Mean and variance are used in a Mixed Integer Programming Model to optimize wastewater treatment plant selection over a long planning horizon (30 years). By fitting our first model to empirical data from an industrial park in Turkey, we find that considering the variance of wastewater load is critical for long-term planning. Also, we quantify the economic significance of lowering wastewater discharges which can be achieved by water recycling or interplant water exchange. © 2023 Elsevier B.V.
