Endüstri Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/204

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Probabilistic assessment of wind power plant energy potential through a copula-deep learning approach in decision trees
(CELL PRESS, 2024) Şahin, Kübra Nur; Sutcu, Muhammed; 0000-0001-9786-6270; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Şahin, Kübra Nur
In the face of environmental degradation and diminished energy resources, there is an urgent need for clean, affordable, and sustainable energy solutions, which highlights the importance of wind energy. In the global transition to renewable energy sources, wind power has emerged as a key player that is in line with the Paris Agreement, the Net Zero Target by 2050, and the UN 2030 Goals, especially SDG-7. It is critical to consider the variable and intermittent nature of wind to efficiently harness wind energy and evaluate its potential. Nonetheless, since wind energy is inherently variable and intermittent, a comprehensive assessment of a prospective site's wind power generation potential is required. This analysis is crucial for stakeholders and policymakers to make well-informed decisions because it helps them assess financial risks and choose the best locations for wind power plant installations. In this study, we introduce a framework based on Copula-Deep Learning within the context of decision trees. The main objective is to enhance the assessment of the wind power potential of a site by exploiting the intricate and non-linear dependencies among meteorological variables through the fusion of copulas and deep learning techniques. An empirical study was carried out using wind power plant data from Turkey. This dataset includes hourly power output measurements as well as comprehensive meteorological data for 2021. The results show that acknowledging and addressing the non-independence of variables through innovative frameworks like the Copula-LSTM based decision tree approach can significantly improve the accuracy and reliability of wind power plant potential assessment and analysis in other real-world data scenarios. The implications of this research extend beyond wind energy to inform decision-making processes critical for a sustainable energy future.
A NEW RATIONAL CLASSIFICATION APPROACH BY THE NEW MIXED DATA BINARIZATION METHOD
(Süleyman Demirel Üniversitesi, 2023) Sütçü, Muhammed; Gülbahar, İbrahim Tümay; 0000-0001-9192-0782; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Sütçü, Muhammed; Gülbahar, İbrahim Tümay
Classification algorithm is a supervised learning technique that is used to identify the category of new observations. However, in some cases, quantitative and qualitative data must be used together. With this approach, we tried to overcome the problems encountered in using quantitative and qualitative data together. In this paper, we model a new classification technique by converting all types of data to binary data because in the real world, data are classified in different types such as binary, numeric, or categorical. By this way, we develop a more accurate and efficient mixed data binarization approach for multi-attribute data classification problems. First, we determine the classes from available dataset and then we classify the new instances into these predetermined classes by using the new proposed data binarization approach. We show how each step of this algorithm could be performed efficiently with a numeric example. Then, we apply the proposed approach on a well-known iris dataset and our model show promising results and improvements over previous approaches.
Karadeniz Bölgesi’nde Kurak ve Nemli Dönemlerin SPI Yöntemi Kullanılarak Belirlenmesi
(Artvin Çoruh Üniversitesi/Artvin Çoruh University, 2024) Öztürk, Yasemin Deniz; Ünlü, Ramazan; 0000-0002-1201-195X; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Ünlü, Ramazan
Karadeniz bölgesi Türkiye’nin en çok yağış alan bölgesidir. Ancak Karadeniz Bölgesi’nde yağışlar hem yıllar arasında hem de bölge içerisinde önemli farklılıklara sahiptir. Bu durum bölgede kuraklıkların yaşanabilmesine ve kurak-nemli dönemlerin birbirini takip etmesine neden olmaktadır. Bu çalışmada yıllık ve 12 aylık SPI değerlerine göre Karadeniz bölgesinde yaşanan kurak ve nemli dönemlerin belirlenmesi amaçlanmıştır. Bölge genelinden seçilen 26 istasyonun 1960-2020 yılları arasındaki ortalama yağış verilerine göre standardize yağış indeksi (SPI) değerleri hesaplanmıştır. Tespit edilen kurak ve nemli dönemlerin eğilimleri MannKendall trend analizi kullanılarak tespit edilmiştir. Ayrıca ısı haritası kullanılarak Karadeniz Bölgesi kıyı ve iç kesimleri olarak ayrılıp kurak ve nemli dönemleri saptanmıştır. Analiz sonuçlarına göre 1966, 1969, 1974-1977, 1984-1986, 1993-1994, 2006-2007 ve 2019- 2020 yıllarının normalden daha az yağış aldığı ve birçok istasyonun kuraklığı şiddetli şekilde olduğu saptanmıştır. 1967, 1988, 1996- 1997, 1999, 2009 ve 2016 yıllarının ise normalden fazla yağış aldığını yani nemli karakterde olduğunu göstermektedir. Mann-Kendall trend analiz sonuçlarına göre Batı Karadeniz Bölgesinin kıyı kesimlerinde azalma eğilimde olduğu saptanmamıştır. Fakat azalışta anlamlılık bulunamamıştır. Orta ve Doğu Karadeniz bölgesinde ise artış eğilimi göstermekle birlikte bu eğilim bazı istasyonlarda anlamlı bulunmuştur. Bölgenin yer şekilleri dolayısıyla genel bir kurak ve genel bir nemli dönem olmadığı, doğu-batı doğrultusu ve kıyı-iç kesimlerde kurak ve nemli dönemlerin farklılık gösterdiği saptanmıştır.
Sustainability assessment of denim fabric made of PET fiber and recycled fiber from postconsumer PET bottles using LCA and LCC approach with the EDAS method
(John Wiley and Sons Inc, 2024) Fidan, Fatma Şener; Aydoğan, Emel Kızılkaya; Uzal, Niğmet; 0000-0002-2397-3628; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Fidan, Fatma Şener; Uzal, Niğmet
The textile industry is under pressure to adopt sustainable production methods because its contribution to global warming is expected to rise by 50% by 2030. One solution is to increase the use of recycled raw material. The use of recycled raw material must be considered holistically, including its environmental and economic impacts. This study examined eight scenarios for sustainable denim fabric made from recycled polyethylene terephthalate (PET) fiber, conventional PET fiber, and cotton fiber. The evaluation based on the distance from average solution (EDAS) multicriteria decision‐making method was used to rank scenarios according to their environmental and economic impacts, which are assessed using life cycle assessment and life cycle costing. Allocation, a crucial part of evaluating the environmental impact of recycled products, was done using cut‐off and waste value. Life cycle assessments reveal that recycled PET fiber has lower freshwater ecotoxicity and fewer eutrophication and acidification impacts. Cotton outperformed PET fibers in human toxicity. Only the cut‐off method reduces potential global warming with recycled PET. These findings indicated that recycled raw‐material life cycle assessment requires allocation. Life cycle cost analysis revealed that conventional PET is less economically damaging than cotton and recycled PET. The scenarios were ranked by environmental and economic impacts using EDAS. This ranking demonstrated that sustainable denim fabric production must consider both economic and environmental impacts. Integr Environ Assess Manag 2024;20:2347–2365. © 2024 The Author(s). Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
A simulation-based approximate dynamic programming approach to dynamic and stochastic resource-constrained multi-project scheduling problem
(Elsevier B.V., 2024) Satic, Ugur; Jacko P.; Kirkbride C.; 0000-0002-9160-0006; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Satic, Ugur
We consider the dynamic and stochastic resource-constrained multi-project scheduling problem which allows for the random arrival of projects and stochastic task durations. Completing projects generates rewards, which are reduced by a tardiness cost in the case of late completion. Multiple types of resource are available, and projects consume different amounts of these resources when under processing. The problem is modelled as an infinite-horizon discrete-time Markov decision process and seeks to maximise the expected discounted long-run profit. We use an approximate dynamic programming algorithm (ADP) with a linear approximation model which can be used for online decision making. Our approximation model uses project elements that are easily accessible by a decision-maker, with the model coefficients obtained offline via a combination of Monte Carlo simulation and least squares estimation. Our numerical study shows that ADP often statistically significantly outperforms the optimal reactive baseline algorithm (ORBA). In experiments on smaller problems however, both typically perform suboptimally compared to the optimal scheduler obtained by stochastic dynamic programming. ADP has an advantage over ORBA and dynamic programming in that ADP can be applied to larger problems. We also show that ADP generally produces statistically significantly higher profits than common algorithms used in practice, such as a rule-based algorithm and a reactive genetic algorithm.
Investigating the carbon border adjustment mechanism transition process with linguistic summarization method: A situational analysis of exporting countries
(ELSEVIER, 2024) Şener Fidan, Fatma; Aydoğan, Sena; Akay, Diyar; 0000-0002-2397-3628; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Şener Fidan, Fatma
The Paris Agreement holds significant importance since it establishes a global framework for addressing the issue of climate change and endeavors to mitigate the release of greenhouse gases. The Carbon Border Adjustment Mechanism was introduced as an integral component of this agreement, aiming to oversee the carbon emissions associated with imported items within the European Union and provide compensation for the emissions from the nations engaged in importation. It is essential to analyze the countries involved in exporting to the European Union within the Carbon Border Adjustment Mechanism context to mitigate carbon leakage and effectively support the objectives outlined in the Paris Agreement. This research investigated 104 nations engaged in exporting activities to 27 European Union member countries. The linguistic summarization method, a descriptive data analytics tool, was employed for the analysis. A total of 42 Combined Nomenclature codes were encompassed within the scope of evaluation throughout the transition phase of the Carbon Border Adjustment Mechanism. This study examines the characteristics of exporting nations based on three variables: The Environmental Performance Index, a sustainability indicator; the Region in which the countries are located as classified by the World Bank; and the quantity of Renewable Energy Consumption. Additionally, the study explores the characteristics of EU countries, focusing on their Environmental Performance Index score and geography. The study employed fuzzy sets and the fuzzy c-means algorithm as parts of the linguistic summarization technique. Polyadic quantifiers were used to extract linguistic summaries, resulting in the acquisition of 124,227 summaries. A total of 1594 summaries have a truth degree exceeding 0.9. The findings were effectively utilized to assess the influence of the linguistic summarization approach and offered a valuable viewpoint for decision-makers needing more expertise in this domain.
Forecasting of the Unemployment Rate in Turkey: Comparison of the Machine Learning Models
(MDPI, 2024) Güler, Mehmet; Kabakçı, Ayşıl; Koç, Ömer; Eraslan, Ersin; Derin, K. Hakan; Güler, Mustafa; Ünlü, Ramazan; Türkan, Yusuf Sait; Namlı, Ersin; 0000-0002-1201-195X; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Ünlü, Ramazan
Unemployment is the most important problem that countries need to solve in their economic development plans. The uncontrolled growth and unpredictability of unemployment are some of the biggest obstacles to economic development. Considering the benefits of technology to human life, the use of artificial intelligence is extremely important for a stable economic policy. This study aims to use machine learning methods to forecast unemployment rates in Turkey on a monthly basis. For this purpose, two different models are created. In the first model, monthly unemployment data obtained from TURKSTAT for the period between 2005 and 2023 are trained with Artificial Neural Networks (ANN) and Support Vector Machine (SVM) algorithms. The second model, which includes additional economic parameters such as inflation, exchange rate, and labor force data, is modeled with the XGBoost algorithm in addition to ANN and SVM models. The forecasting performance of both models is evaluated using various performance metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The findings of the study show how successful artificial intelligence methods are in forecasting economic developments and that these methods can be used in macroeconomic studies. They also highlight the effects of economic parameters such as exchange rates, inflation, and labor force on unemployment and reveal the potential of these methods to support economic decisions. As a result, this study shows that modeling and forecasting different parameter values during periods of economic uncertainty are possible with artificial intelligence technology.
Symbolic Aggregate Approximation-Based Clustering of Monthly Natural Gas Consumption
(Bitlis Eren Üniversitesi, 2024) Nalici, Mehmet Eren; Söylemez, İsmet; Ünlü, Ramazan; 0000-0002-7954-6916; 0000-0002-8253-9389; 0000-0002-1201-195X; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Nalici, Mehmet Eren; Söylemez, İsmet; Ünlü, Ramazan
Natural gas is an indispensable non-renewable energy source for many countries. It is used in many different areas such as heating and kitchen appliances in homes, and heat treatment and electricity generation in industry. Natural gas is an essential component of the transportation sector, providing a cleaner alternative to traditional fuels in vehicles and fleets. Moreover, natural gas plays a vital role in boosting energy efficiency through the development of combined heat and power systems. These systems produce electricity and useful heat concurrently. As nations move towards more sustainable energy solutions, natural gas has gained prominence as a transitional fuel. This is due to its lower carbon emissions when compared to coal and oil, thus making it an essential component of the global energy framework. In this study, monthly natural gas consumption data of 28 different European countries between 2014 and 2022 are used. Symbolic Aggregate Approximation method is used to analyse the data. Analyses are made with different numbers of segments and numbers of alphabet sizes, and alphabet vectors of each country are created. These letter vectors are used in hierarchical clustering and dendrogram graphs are created. Furthermore, the elbow method is used to determine the appropriate number of clusters. Clusters of countries are created according to the determined number of clusters. In addition, it is interpreted according to the consumption trends of the countries in the determined clusters.
Generating Linguistic Advice for the Carbon Limit Adjustment Mechanism
(SPRINGER, 2024) Fidan, Fatma Şener; Aydoğan, Sena; Akay, Diyar; 0000-0002-2397-3628; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Fidan, Fatma Şener
Linguistic summarization, a subfield of data mining, generates summaries in natural language for comprehending big data. This approach simplifies the incorporation of information into decision-making processes since no specialized knowledge is needed to understand the generated language summaries. The present research employs linguistic summarization to examine the circumstances surrounding the Carbon Border Adjustment Mechanism, one of the most significant regulations confronting exporting nations to the European Union, and will be adopted to support sustainable growth. In this paper, associated with several attributes of the countries and product flow from exporting countries to European countries were defined as nodes and relations, respectively. Before the modeling phase, fuzzy c-means automatically identified fuzzy sets and membership degrees of attributes. During the modeling phase, summary forms were generated using polyadic quantifiers. A total of 1944 linguistic summaries were produced between exporting countries and European countries. Thirty-five summaries have a truth degree greater than or equal to the threshold value of 0.9, which is considered reasonable. The provision of natural language descriptions of the Carbon Border Adjustment Mechanism is intended to aid decision-makers and policymakers in their deliberations.
A bi-criteria approach to scheduling in the face of uncertainty: Considering robustness and stability simultaneously
(Nova Science Publishers, Inc., 2014) Selcuk, Gören; Sabuncuoĝlu, Ihsan; 000-0002-5320-4213; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Selcuk, Gören; Sabuncuoĝlu, Ihsan
It is possible to scrutinize impacts of uncertainty on schedules from two different perspectives. The flrst one has to do with the fact that schedules are required to main- tain high performance in the face of uncertainty. In other words, it is desired that their performances are insensitive to negative impacts of disruptions. We refer to this view- point as the robustness perspective. The second viewpoint is about another quality: when a schedule is executed in the shop floor, the realized schedule is required not to deviate much from its initial version. This is because many activities besides pro- duction are planned based on the production schedule. It is important that unforeseen disruptions affect the plans for these activities as little as possible. We refer to this viewpoint as the stability perspective. Even though a considerable body of literature has emerged on hedging schedules against the negative effects of unforeseen disrup- tions in the last two decades, few studies address the problem of scheduling under uncertainty from both the robustness and the stability perspectives at the same time. The nature of the relation between robustness and stability, the trade-off between them, the circumstances under which they conflict or reconcile need to be thoroughly inves- tigated. To this end, we propose a bi-criteria approach to simultaneously investigate the robustness and stability of production schedules. We consider proactive schedul- ing in a single machine environment with random processing times. We use the total expected flow time and the total variance of job completion times as the robustness and stability measures, respectively. The proposed o-constraint variants are exact methods to generate the set of all Pareto-optimal schedules. We also develop an algorithm to generate a flxed number (set by the decision-maker) of near-Pareto-optimal schedules to deflne the characteristics and the shape of the trade-off curve without generating the entire Pareto set. Our computational experiments indicate that the proposed algorithms are efflcient.
Solving an ammunition distribution network design problem using multi-objective mathematical modeling, combined AHP-TOPSIS, and GIS
(ELSEVIER, 2019) Akgün, İbrahim; Erdal, Hamit; 0000-0001-6325-7741; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Akgün, İbrahim
We study a strategic-level ammunution distribution network design problem (ADNDP) where the purpose is to determine the locations and the service assignments of main, regional, and local depots in order to meet the ammunition needs of military units considering several factors, e.g., stock levels at the depots, costs, and risk levels of depot locations. ADNDP is a real-world and large-scale problem for which scientific decision making methods do not exist. We propose a methodology that uses multi-objective mathematical modeling, Analytic Hierarchy Process (AHP), The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Geographic Information System (GIS) to solve the problem. The multi-objective mathematical model determines the locations and the service assignments of depots considering two objectives, namely, to minimize transportation costs and to minimize risk scores of main depot locations. The risk score of a depot location indicates how vulnerable the location is to disruptions and is determined by a combined AHP-TOPSIS analysis where TOPSIS is used to compute the risk scores and AHP is used to compute the weights needed by TOPSIS for the identified risk attributes. The GIS analysis is conducted to determine the potential depot locations using map layers based on spatial criteria. We have applied the proposed methodology in designing and evaluating a real ammunition distribution network under different scenarios in collaboration and cooperation with the area experts. We have employed the weighted-sum method to find non-dominated solutions for each scenario and discussed their tradeoffs with the area experts. The purpose of this paper is to present the proposed methodology, findings, and insights.
The impact of organic cotton use and consumer habits in the sustainability of jean production using the LCA approach
(SPRINGER, 2023) Şener Fidan, Fatma; Kızılkaya Aydoğan, Emel; Uzal, Niğmet; 0000-0002-2397-3628; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Şener Fidan, Fatma; Uzal, Niğmet
Due to the rise in clothing consumption per person and growing consumer awareness of environmental issues with products, the textile industry must adopt new practices for improving sustainability. The current study thoroughly investigates the benefts of using organic cotton fber instead of conventional cotton fber. Because of the extensive use of natural resources in the production of cotton, the primary raw material for textiles, which accounts for the environmental efects of a pair of jeans, a life cycle assessment methodology was used to examine these efects in four diferent scenarios. The additional scenarios were chosen based on the user preferences for washing temperatures, drying methods, and the type of cotton fber used in the product. The environmental impact categories of global warming potential, eutrophication potential terrestrial ecotoxicity potential, acidifcation potential, and freshwater ecotoxicity potential were analyzed by the CML-IA method. The life cycle assessment results revealed that the lowest environmental impacts were obtained for scenario 4 with 100% organic cotton fber with an improvement of 87% in terrestrial ecotoxicity potential and 59% in freshwater ecotoxicity potential. All of the selected environmental impacts of a pair of jeans are reduced in all scenarios when organic cotton is used. Additionally, consumer habits had a signifcant impact on all impact categories. Using a drying machine instead of a line dryer during the use phase is just as important as the washing temperature. The environmental impact hotspots for a pair of jeans were revealed to be the eutrophication potential, acidifcation potential, and global warming potential categories during the use phase, and the terrestrial ecotoxicity potential and freshwater ecotoxicity potential categories during the fabric manufacturing including cotton cultivation. The use of organic cotton as a raw material in manufacturing processes, as well as consumer preferences for washing temperature and drying methods, appears to have signifcant environmental impacts on a pair of jeans’ further sustainable life cycle.
Proje Yönetimi Kapsamında Serim Kesme/Önleme Modellerinin ve Çözüm Yöntemlerinin Geliştirilmesi
(TUBİTAK, 2017) Akgün, İbrahim; 0000-0001-6325-7741; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Akgün, İbrahim
Serim/Şebeke Kesme/Önleme (Problemi (SKP)’nde, serim kullanıcısı ve önleyici olmak üzere birbiri hakkında yeterli bilgiye sahip iki rakip bulunmaktadır. Serim kullanıcısı, işlettiği serimi optimal şekilde kullanmak isterken; önleyici, serim kullanıcısının serimi etkin şekilde kullanmasını elindeki kısıtlı kaynaklarla önlemeye çalışır. SKP’nin, uyuşturucu trafiğini engellemek için timlerin konuşlandırılacağı yerlerin tespit edilmesinden hava füze savunması için antibalistik füzelerin yerlerinin seçilmesine, bir şehrin elektrik şebekesindeki kritik noktaların bulunmasından bir hastalığın yayılmasını engellemek için alınması gereken tedbirlere kadar çok farklı yelpazede uygulamaları mevcuttur. Diğer yandan, ortaya çıkan iki seviyeli matematiksel modellerin çözümü zordur ve özel yöntemlerin geliştirilmesini gerektirmektedir. Bu nedenlerle, SKP birçok araştırmacının ilgi odağı haline gelmiş ve bu durum çalışmamızın da motivasyon kaynağı olmuştur. Bu projede, SKP, özel olarak proje yönetimi kapsamında ele alınmıştır. Literatürde, proje şebekelerinde SKP’nin uygulanmasına ilişkin sadece iki çalışma bulunmaktadır. Her iki çalışmada, temel ve hızlandırılmış CPM modelleri esas alınmıştır. Proje şebekelerinin çok farklı türleri olduğu ve çok geniş bir yelpazede uygulama alanının olması hususları birlikte değerlendirildiğinde, literatürde çok önemli bir boşluk olduğu görülmektedir. Bu çalışmanın amacı da, söz konusu tespitten hareketle, proje şebekelerinde önleme konusuna sistematik ve bütüncül bir yaklaşım geliştirmektir. Bu bağlamda, modelleme açısından birbirinden farklılıklar arz eden proje şebekeleri için önleme modelleri ve çözüm yöntemleri geliştirilmiştir. Çalışmada, temel ve hızlandırılmış CPM, zaman/maliyet takas problemi kapsamında CPM, yenilenebilir kaynak durumunda CPM ve PERT tabanlı proje şebekeleri ele alınmıştır. Anılan problemler için, ilk olarak iki seviyeli (maks-min) önleme modelleri geliştirilmiştir. Müteakiben, iki seviyeli modellerin bazıları, dualite özelliğinden istifade edilerek, optimizasyon programları ile çözülebilecek tek seviyeli hale getirilmiştir. Dualite özelliğinin kullanılamadığı problemler için, ayrıştırma algoritmaları geliştirilmiştir. Modeller ve ayrıştırma algoritmaların performansları, çeşitli problemler kullanılarak test edilmiştir.
Tesis yeri seçim problemleri için akış tabanlı modellerin ve çözüm metodolojilerinin geliştirilmesi
(TUBİTAK, 2017) Akgün, İbrahim; Gören, Selçuk; Kara, Bahar Yetiş; 0000-0001-6325-7741; 0000-0002-5320-4213; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Akgün, İbrahim; Gören, Selçuk
Tesis yeri seçim problemleri, yoğun olarak akademik çalışmaların yürütüldüğü alanlardan biridir. Ancak, bazı araştırmacılar tarafından, tesis yeri seçim modellerinin gerçek hayat uygulamalarını temsil etme ve çözmedeki yeterliliği uzun süredir sorgulanmakta ve yeni modellerin geliştirilmesine ihtiyaç olduğu ifade edilmektedir. Literatürdeki modellerin büyük bir çoğunluğu, modellerin gerçek hayattaki uygulama alanlarını sınırlandıran belirli varsayımlara dayanmaktadır. Bu varsayımların en önemlilerinden biri, modellerde girdi olarak kullanılan serim ve veri yapısıyla ilgilidir. Literatürdeki modeller, düğümler arası mesafe matrisinde en kısa yol uzunluklarının kullanıldığı tam serim (complete network) yapısı üzerine kuruludur. Modellerde tam serim yapısının kullanılması, gerçek hayattaki serimlerin (örneğin, demiryolları ya da karayolları) tam serim yapısında olmasından ziyade, araştırmacıların bazen doğrudan bazen de dolaylı olarak kabul ettiği bir varsayıma dayanmaktadır. Araştırmacılar, gerçek hayat serimlerine en kısa yol algoritmalarının uygulanması suretiyle, düğümler arasında en kısa yolların kullanıldığı bir tam serim yapısının oluşturulduğunu varsaymaktadır. Diğer bir ifadeyle, modellerde girdi olarak kullanılan serim yapısı, düğümler arası mesafelerin üçgen eşitsizliğini sağladığı tam serimdir. Bu yaklaşım genel olarak kabul görmekle beraber, gerçek serim ve veri yapısının modellerde doğrudan girdi olarak kullanılmaması, modelleme ve çözüm açısından bazı dezavantajlara sebep olmaktadır. Daha da önemlisi, gerçek hayatta en kısa yolların tercih edilmediği veya üçgen eşitsizliğinin sağlanmadığı birçok durum vardır. Söz konusu tespitlerden hareketle, literatürdeki yaklaşımlardan tamamen farklı olarak, tam olmayan gerçek serim yapısının modellerde doğrudan girdi olarak kullanıldığı tesis yeri seçim problemleri tanımlanmıştır. Projede, tesis yeri seçiminde klasikler arasında kabul edilmeleri ve diğer tesis yeri seçim modellerinin temelini oluşturmaları nedeniyle, p-ortanca ve p-hub ortanca problemleri ele alınmıştır. Bu problemlerin, ayrıt/düğüm kapasiteli, kapasitesiz, tek ve çoklu atama ile farklı topolojilere izin veren versiyonları için modeller ve çözüm yöntemleri geliştirilmiştir. Geliştirilen modeller, hem gerçek serim yapısı, hem de (üçgen eşitsizliğini sağlamayan dahil) tam serim yapısı ile doğru sonuçlar vermektedir. Geliştirilen formülasyonlarda, daha çok tesis-talep noktası atama kararlarına dayanan literatürdeki modellerin aksine, ayrıt tabanlı akışlar esas alınmıştır. Modellerin çözümü için, Benders Ayrıştırma ve Lagrange gevşetme algoritmaları geliştirilmiştir. Modellerin ve geliştirilen algoritmaların performansları, çeşitli problemler kullanılarak test edilmiştir.
Analysis of under-five mortality by diseases in countries with different levels of development: a comparative analysis
(Prusa Medikal Yayıncılık, 2023) Sütçü, Muhammed; Güner, Pınar; Ersöz, Nur Şebnem; 0000-0002-8523-9103; 0000-0001-5979-0375; 0000-0003-3343-9936; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Sütçü, Muhammed; Güner, Pınar; Ersöz, Nur Şebnem
Objectives: The right to health is critical for children because they are sensitive beings who are more susceptible to disease and health problems. It would be beneficial to compare child mortality rates in countries with different levels of development and to conduct studies to address them by taking into account their causes. This study aims to analyze the situation of developed, developing and least developed countries in terms of causes under-5 child mortality (U5CM) determined by World Health Organization and to identify the similarities or differences of under-five mortality. Methods: Child mortality rates per 1,000 live births between 2000 and 2017 years in between different age groups (0-27 days and 1-59 months) by causes (disease-specific) were obtained from World Health Organization for a total 15 countries including developed, developing and least developed countries. Regression analysis was performed to identify which causes have more impact on child mortality. In addition, the relationship between diseases was calculated using Euclidean distance, and diseases were clustered using k-means clustering algorithm for each country. Results: As a result of mathematical and statistical analysis, it was seen that causes of child mortality have a significant relation with the development level of country where a child was born. Conclusions: It has been observed that the causes of child mortality in countries with different levels of development vary depending on different factors such as geographical conditions, air quality population and access to medicine.
A simulation-based approximate dynamic programming approach to dynamic and stochastic resource-constrained multi-project scheduling problem
(ELSEVIER, 2024) Satic, U.; Jacko, P.; Kirkbride, C.; 0000-0002-9160-0006; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Satic, U.
We consider the dynamic and stochastic resource-constrained multi-project scheduling problem which allows for the random arrival of projects and stochastic task durations. Completing projects generates rewards, which are reduced by a tardiness cost in the case of late completion. Multiple types of resource are available, and projects consume different amounts of these resources when under processing. The problem is modelled as an infinite-horizon discrete-time Markov decision process and seeks to maximise the expected discounted long-run profit. We use an approximate dynamic programming algorithm (ADP) with a linear approximation model which can be used for online decision making. Our approximation model uses project elements that are easily accessible by a decision-maker, with the model coefficients obtained offline via a combination of Monte Carlo simulation and least squares estimation. Our numerical study shows that ADP often statistically significantly outperforms the optimal reactive baseline algorithm (ORBA). In experiments on smaller problems however, both typically perform suboptimally compared to the optimal scheduler obtained by stochastic dynamic programming. ADP has an advantage over ORBA and dynamic programming in that ADP can be applied to larger problems. We also show that ADP generally produces statistically significantly higher profits than common algorithms used in practice, such as a rule-based algorithm and a reactive genetic algorithm.
Türkiye’de Yapılan Kuraklık Analiz Çalışmaları Üzerine Bir Derleme
(Ankara Üniversitesi, 2022) DENİZ ÖZTÜRK, YASEMİN; ÜNLÜ, RAMAZAN; 0000-0002-1201-195X; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; ÜNLÜ, RAMAZAN
Kuraklık, iklim değişikliği konusunun önem kazanmasıyla birlikte, özellikle 2000’li yıllardan sonra bilim insanları tarafından en çok çalışılan afet konularından birisi olmuştur. Kuraklık konusunda birçok farklı yöntemin bulunması ve kuraklığın çok farklı bilim dalları tarafından incelenmesi sayesinde kuraklık konusunda çok fazla bilimsel yayın üretilmiştir. Bu çalışmada, meteorolojik veriler üzerinden herhangi bir istatistiksel yöntem kullanılarak Türkiye’nin geneli ya da bir bölgesiyle ilgili kuraklık analizlerinin yer aldığı tezler, ulusal makaleler ve uluslararası makaleler derlenmiştir. Çalışmada 1943-2021 arasında yazılmış 73 yüksek lisans ve doktora tezi, 107 ulusal makale ve 90 adet uluslararası makale olmak üzere toplam 270 çalışma incelenmiştir. Bu çalışmalar yayın yılı, kullanılan kuraklık analiz yöntemleri, ilk yazarın bilim alanı ve çalışmada incelenen bölgeye göre sınıflandırılarak frekans dağılımları ortaya konulmuştur. Çalışmada ulaşılan başlıca sonuçlar şu şekildedir: Türkiye de kuraklık analizi ile ilgili yayınlanan ilk çalışmalar 1943, 1956 ve 1965 yıllarında yapılmış olmasına rağmen kuraklık ile ilgili çalışmalar 2000 yılı sonrasında artış göstermeye başlamıştır. Toplam yayın sayısı 2019’da 37, 2020’de 43 adet, 2021’de 64 adede ulaşmıştır. 2019-2021 döneminde yapılan yayınlar tüm yayınların %53’lük kesimine karşılık gelmektedir. Son yıllardaki bu hızlı artış yayın sayılarında logaritmik artışın yaşanmasına neden olmuştur. Çalışmalarda kuraklık analizlerinde 63 farklı yöntem kullanılmakla birlikte standartlaştırılmış yağış indisi %56’lık bir kullanım oranı ile baskın yöntem olmaktadır. Türkiye genelini kapsayan çalışmalar olmakla birlikte (41 adet), çalışmaların büyük bölümü havza bazlı gerçekleştirilmiştir (113 adet). Diğer çalışmalar ise coğrafi bölgeler, il ya da daha küçük yerleşim alanları için gerçekleştirilmiştir. Farklı bilim alanlarına göre İnşaat Mühendisliği (131 adet) ve Coğrafya bölümleri (41 adet) en fazla kuraklık analizi çalışmaları gerçekleştiren bölümlerdir.
The selection of washing machine programs with fuzzy dematel and moora-ratio multi-criteria decision-making methods considering environmental and cost criteria
(ELSEVIER, 2024) Fidan, Fatma Şener; Aydoğan, Emel Kızılkaya; Uzal, Nigmet; 0000-0002-2397-3628; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Fidan, Fatma Şener; Uzal, Nigmet
The washing machine is the prevalent white household equipment in contemporary society. These machines provide consumers with a range of program options that encompass several variables, including temperature and detergent type. Nevertheless, the selection made by individual customers about the washing machine program they opt for carries substantial environmental consequences during the use stage of textile products. According to studies on the life cycle of clothes, it has been established that the use stage, following the extraction of raw materials, exerts the most substantial influence on environmental impacts. The objective of this research is to assess the washing machine programs provided by the manufacturer through the application of a comprehensive systematic approach for analysis. The evaluation of scenarios for washing machine programs was conducted using the MOORA-Ratio multi-criteria decision-making process. This evaluation considered various parameters, including environmental impact and cost. The life cycle assessment methodology was employed to quantify the environmental impact of the specified criteria. Based on the comprehensive study conducted by integrating criteria across numerous dimensions, it has been determined that the most favorable scenario wass scenario 1, which was developed for the Cotton 20 C program. The primary objective of this research endeavor is to fill a significant need in the current body of literature by undertaking a comprehensive review of washing machine programs that have not been previously recorded. This study employs a comprehensive methodology to investigate the environmental and economic implications linked to these activities, with the objective of delivering significant insights to producers and users.
Parameter uncertainties in evaluating climate policies with dynamic integrated climate-economy model
(SPRINGER, 2024) Sütçü, Muhammed; 0000-0002-8523-9103; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Sütçü, Muhammed
Climate change is a complex issue with signifcant scientifc and socio-economic uncertainties, making it difcult to assess the efectiveness of climate policies. Dynamic Integrated Climate-Economy Models (DICE models) have been widely used to evaluate the impact of diferent climate policies. However, since climate change, long-term economic development, and their interactions are highly uncertain, an accurate assessment of investments in climate change mitigation requires appropriate consideration of climatic and economic uncertainties. Moreover, the results of these models are highly dependent on input parameters and assumptions, which can have signifcant uncertainties. To accurately assess the impact of climate policies, it is crucial to incorporate uncertainties into these models. In this paper, we explore the impact of parameter uncertainties on the evaluation of climate policies using DICE models. Our goal is to understand whether uncertainty signifcantly afects decision-making, particularly in global warming policy decisions. By integrating climatic and economic uncertainties into the DICE model, we seek to identify the cumulative impact of uncertainty on climate change. Overall, this paper aims to contribute to a better understanding of the challenges associated with evaluating climate policies using DICE models, and to inform the development of more efective policy measures to address the urgent challenge of climate change.
Comparative life cycle assessment of retort pouch and aluminum can for ready-to-eat bean packaging
(SPRINGER, 2023) Gulcimen, Sedat; Ozcan, Ozlem; Cevik, Selin Babacan; Kahraman, Kevser; Uzal, Nigmet; 0000-0002-8967-3484; 0000-0002-2786-3944; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Gulcimen, Sedat; Ozcan, Ozlem; Kahraman, Kevser; Uzal, Nigmet
Since packaging contributes to severe environmental impacts in food production, alternatives of packaging materials that satisfy customer needs while minimizing environmental impacts in a cost-effective manner should be preferred for food product sustainability. This paper compares two different packaging materials (aluminum cans and retort pouches) with a life cycle approach to assess the environmental impacts of ready-to-eat bean packaging. The life cycle assessment (LCA) was used to define and compare the environmental performance of ready-to-eat beans in aluminum cans and retort pouches. The gate-to-gate approach was used in the LCA, with a functional unit of 1 kg of packaged ready-to-eat bean product. Inventory for packaging in retort pouch was created in collaboration with Duru Bulgur Company (Karaman, Turkey) and the data for ready-to-eat beans in the aluminum can were gathered from the literature. The findings show that ready-to-eat beans in retort pouches have lower environmental impacts than ready-to-eat beans in aluminum cans. The packaging and washing processes for both ready-to-eat beans packaged in aluminum cans and retort pouches had the greatest environmental impact. In ready-to-eat beans production, retort pouch provides 87% better environmental performance than aluminum can in terms of global warming (GW). Overall, the results demonstrated that replacing aluminum cans with retort pouches in ready-to-eat bean production can significantly reduce environmental effects in all impact categories.

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