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Article Borulu Sulama Şebekeleri Optimizasyonu(Turkish Chamber Civil Engineers, 2018) Marım, Gökhan; Darama, Yakup; Bozkuş, ZaferBorulu sulama şebekeleri ülkelerin tarımsal ürün yetiştirmesinde ve su tasarrufunda enönemli sistemlerdir. Günümüzde tarımsal amaçlı sulama, su tüketiminin en yüksek olduğusektördür. Ülkemizde tarım sektörünün kullandığı su miktarı su potansiyelimizin %73oranındadır. Ülkemizde ve genelde Dünyada nüfus artışı nedeniyle tarımsal üretimde sutalebinin artması ve su kaynaklarımızın sınırlı olması nedeniyle sürdürülebilir su kaynaklarıyönetimi zorunlu olmaktadır. Son yıllarda ülkemizde yapılan sulama sistemleri yatırımlarınınbüyük bir çoğunluğunu, su kaybını ve tarımsal su kullanımını azaltan modern borulu sulamaşebekeleri yatırımları oluşturmaktadır. Bu çalışma borulu sulama şebekelerinintasarımlarının maliyet ve istenen işletme basınçları açısından optimum koşullara ulaşmasınaodaklanmıştır. Optimizasyon problemi çözümünde heuristik tabanlı dinamik programlamaile birlikte doğrusal programlama yöntemi olan “Simplex” metodu kullanılmış olup, buoptimizasyon yazılımı DSİ borulu sulama şebekeleri için uygulanmıştır.Article Citation - WoS: 25Citation - Scopus: 29Optimum Design of Steel Braced Frames Considering Dynamic Soil-Structure Interaction(Springer, 2019) Bybordiani, Milad; Azad, Saeid Kazemzadeh; Kazemzadeh Azad, SaeidRecent studies on design optimization of steel frames considering soil-structure interaction have focused on static loading scenarios, and limited work has been conducted to address the design optimization under dynamic soil-structure interaction. In the present work, first, a platform is developed to perform optimization of steel frames under seismic loading considering dynamic soil-structure interaction (SSI) in order to quantify the effects of earthquake records on the optimum design. Next, verification of the adopted modeling technique is conducted using comparison of the results with the reference solution counterparts in frequency domain. For time history analyses, records from past events are selected and scaled to a target spectrum using simple scaling approach as well as spectrum matching technique. For sizing of the steel frames, a recently developed metaheuristic optimization algorithm, namely exponential big bang-big crunch optimization method, is employed. To alleviate the computational burden of the optimization process, the metaheuristic algorithm is integrated with the so-called upper bound strategy. Effects of factors such as the building height, presence of soil domain, and the utilized ground motion scaling technique are investigated and discussed. The numerical results obtained based on 5- and 10-story steel braced frame dual systems reveal that, although dynamic SSI reduced the seismic demands to some extent, given the final design pertains to different load combinations, the optimum weight difference is not considerable.Article Citation - WoS: 7Citation - Scopus: 12Genetic Algorithm and Tabu Search Memory With Course Sandwiching (gats_cs) for University Examination Timetabling(Tech Science Press, 2020) Abayomi-Alli, A.; Misra, S.; Fernandez-Sanz, L.; Abayomi-Alli, O.; Edun, A. R.University timetable scheduling is a complicated constraint problem because educational institutions use timetables to maximize and optimize scarce resources, such as tine and space. In this paper, an examination timetable system using Genetic Algorithm and Tabu Search memory with course sandwiching (GAT_CS), was developed fora lame public University. The concept of Genetic Algorithm with Selection and Evaluation was implemented while the memory properties of Tabu Search and course sandwiching replaced Crossover and Mutation. The result showed that GAT_CS had hall allocation accuracies of 96.07% and 99.02%, unallocated score of 3.93% and 0.98% for first and second semesters, respectively. It also automatically sandwiched (scheduled) multiple examinations into single halls with a simulation time in the range of 20-29.5 seconds. The GAT_CS outperformed previous related works on the same timetable dataset. It could, however, be improved to reduce clashes, duplications, multiple examinations and to accommodate more system-defined constraints.Conference Object A Lithium-Ion Battery Fast Charging Algorithm Based on Electrochemical Model: Experimental Results(Amer Soc Mechanical Engineers, 2024) Anwar, Sohel; Pramanik, Sourav; Amini, AliLithium-Ion batteries have become the principal battery technology for EVs to date. However, one of the principal factors limiting the widespread usage of the EVs is the length of charging times for the lithium-ion battery packs. The appropriate charging algorithm is critical to shorten the battery charging times while keeping the battery safe. In our earlier work, we proposed a novel optimal strategy for charging the lithium-ion battery based on electrochemical battery model using A performance index that aimed at achieving a faster charging rate while maintaining safe limits for various battery parameters. A more realistic model, based on battery electro-chemistry has been used for the design of the optimal charging algorithm as opposed to the conventional equivalent circuit models. Simulation results showed that the proposed optimal charging algorithm is capable of shortening the charging time of a lithium-ion cell by as much as 30% when compared with the standard constant current charging. Here we present the results from a number of experiments using Lithium-Ion cylindrical cells that were charged using the proposed algorithm and compared the charging times with the standard constant current-constant voltage (CC-CV) charging algorithms. A Maccor Series 4300 battery testing system was used to carry out the experiments. The experimental results showed that the proposed algorithm offered shorter charging times by up to 16% when compared to the CC-CV charging algorithms under the same battery initial conditions such as SOC and temperature of the cells.Article Citation - WoS: 24Activity Uncrashing Heuristic With Noncritical Activity Rescheduling Method for the Discrete Time-Cost Trade-Off Problem(Asce-amer Soc Civil Engineers, 2020) Sonmez, Rifat; Aminbakhsh, Saman; Atan, TankutDespite intensive research efforts that have been devoted to discrete time-cost optimization of construction projects, the current methods have very limited capabilities for solving the problem for real-life-sized projects. This study presents a new activity uncrashing heuristic with noncritical activity rescheduling method to narrow the gap between the research and practice for time-cost optimization. The uncrashing heuristic searches for new solutions by uncrashing the critical activities with the highest cost-slope. This novel feature of the proposed heuristic enables identification and elimination of the dominated solutions during the search procedure. Hence, the heuristic can determine new high-quality solutions based on the nondominated solutions. Furthermore, the proposed noncritical activity rescheduling method of the heuristic decreases the amount of scheduling calculations, and high-quality solutions are achieved within a short CPU time. Results of the computational experiments reveal that the new heuristic outperforms state-of-the-art methods significantly for large-scale single-objective cost minimization and Pareto front optimization problems. Hence, the primary contribution of the paper is a new heuristic method that can successfully achieve high-quality solutions for large-scale discrete time-cost optimization problems.Review Citation - Scopus: 2Coal Preparation in the World - Current Status and Global Trends: a Review("Ore and Metals" Publishing house, 2016) Rubinstein,J.B.; Swanson,A.; Holuszko,M.E.; Shaoqiang,Z.; Ziaja,D.; Anastassakis,G.; Vorobev,S.A.This article is a review composed of 14 sections prepared by representatives of the involved countries. The sections inform on: coal production volume per country; principal coal producing regions and companies; coal preparation technologies and trends of coal use in national economies, considering the environmental constraints. The review opens with the section devoted to the state of the art and prospects of coal preparation in Russia; the next sections about other countries are arranged in the way to fit the Latin alphabet. The scope of the Russian section encompasses large projects on coal preparation, prospects of coal application in power generation and the issue of coal mine waste reprocessing. The Australian section emphasizes that coal is an important export article and the key component of power generation in the country. It is mentioned that round 90 % of ROM coal needs preparation before marketing. The section on Canada gives evaluation of coal reserves and resources and a detail description of coalproducing companies in the country. China is the largest coal-producing country in the world (3.87 Bt of coal in 2014); more than 60 % of coal is subjected to preparation. Germany is running short of coal reserves (coal reserves are only sufficient until late 2018) but holds enormous reserves of lignite subjected to open pit mining. Hungary produces nearly 10 Mt of coal yearly and uses it to generate 14 % of the total power output. India is the world's third coal producer (after China and USA as of 2014). Kazakhstan takes half of produced coal to generate power and 30 % for export. Poland is the largest coal producer in Europe. All coal is mined with the underground method and approximately 60 % of coal needs preparation. The Republic of South Africa exports nearly one third of produced coal. Half of coal left in the country is spent to generate power and round 20 % of coal is converted to chemicals and fuel products. The best part of the produced coal needs preparation and coal for export is totally subjected to dressing. Turkey mines mainly lignite (95 %). The deficit of power-generating coal is compensated by the import. The coal industry of the Great Britain is at the stage of dying. It is planned to close all coal-run power plants by 2025. USA is the world's second producer of coal. Preparation embraces approximately 40 % of mined coal. The review ends with an analysis of international RandD projects in the area of coal preparation.Article Citation - WoS: 15Citation - Scopus: 17Performance Evaluation of Laser Induced Breakdown Spectroscopy in the Measurement of Liquid and Solid Samples(Pergamon-elsevier Science Ltd, 2018) Bilge, Gonca; Sezer, Banu; Boyaci, Ismail Hakki; Eseller, Kemal Efe; Berberoglu, HalilLiquid analysis by using LIBS is a complicated process due to difficulties encountered during the collection of light and formation of plasma in liquid. To avoid these, some applications are performed such as aerosol formation and transforming liquid into solid state. However, performance of LIBS in liquid samples still remains a challenging issue. In this study, performance evaluation of LIBS and parameter optimizations in liquid and solid phase samples were performed. For this purpose,milk was chosen as model sample; milk powder was used as solid sample, and milk was used as liquid sample in the experiments. Different experimental setups have been constructed for each sampling technique, and optimizations were performed to determine suitable parameters such as delay time, laser energy, repetition rate and speed of rotary table for solid sampling technique,and flow rate of carrier gas for liquid sampling technique. Target element was determined as Ca, which is a critically important element in milk for determining its nutritional value and Ca addition. In optimum parameters, limit of detection (LOD), limit of quantification (LOQ) and relative standard deviation (RSD) values were calculated as 0.11%, 0.36% and 8.29% respectively for milk powders samples; while LOD, LOQ and RSD values were calculated as 0.24%, 0.81%, and 10.93% respectively for milk samples. It can be said that LIBS is an applicable method in both liquid and solid samples with suitable systems and parameters. However, liquid analysis requires much more developed systems for more accurate results. (C) 2018 Elsevier B.V.All rights reserved.Article Citation - WoS: 93Citation - Scopus: 106Optimization of Electric Vehicle Recharge Schedule and Routing Problem With Time Windows and Partial Recharge: a Comparative Study for an Urban Logistics Fleet(Elsevier, 2021) Bac, Ugur; Baç, Uğur; Erdem, Mehmet; Erdem, Mehmet; Baç, Uğur; Erdem, Mehmet; Industrial Engineering; Industrial EngineeringThe use of electric vehicles (EVs) is becoming more and more widespread and the interest in these vehicles is increasing each day. EVs promise to emit less air pollution and greenhouse gas (GHG) emissions with lower operational costs when compared to fossil fuel-powered vehicles. However, many factors such as the limited mileage of these vehicles, long recharging times, and the sparseness of available recharging stations adversely affect the preferability of EVs in industrial and commercial logistics. Effective planning of EV routes and recharge schedules is vital for the future of the logistics sector. This paper proposes an electric vehicle routing problem with the time windows (EVRPTW) framework, which is an extension of the well-known vehicle routing problem (VRP). In the proposed model, partial recharging is considered for the EVRPTW with the multiple depots and heterogeneous EV fleet and multiple visits to customers. While routing a set of heterogeneous EVs, their limited ranges, interdependent on the battery capacity, should be taken into consideration and all the customers' deliveries should be completed within the predetermined time windows. To deal with this problem, a series of neighbourhood operators are developed for the local search process in the variable neighbourhood search (VNS) and variable neighbourhood descent (VND) heuristics. The proposed solution algorithms are tested in large-scale instances. Results indicate that the proposed heuristics perform well as to this problem in terms of optimizing recharging times, idle waiting times, overtime of operators, compliance with time windows, number of vehicles, depots, and charging stations used.Article Citation - WoS: 33Citation - Scopus: 41Backhaul-Aware Optimization of Uav Base Station Location and Bandwidth Allocation for Profit Maximization(Ieee-inst Electrical Electronics Engineers inc, 2020) Cicek, Cihan Tugrul; Gultekin, Hakan; Tavli, Bulent; Yanikomeroglu, HalimUnmanned Aerial Vehicle Base Stations (UAV-BSs) are envisioned to be an integral component of the next generation Wireless Communications Networks (WCNs) with a potential to create opportunities for enhancing the capacity of the network by dynamically moving the supply towards the demand while facilitating the services that cannot be provided via other means efficiently. A significant drawback of the state-of-the-art have been designing a WCN in which the service-oriented performance measures (e.g., throughput) are optimized without considering different relevant decisions such as determining the location and allocating the resources, jointly. In this study, we address the UAV-BS location and bandwidth allocation problems together to optimize the total network profit. In particular, a Mixed-Integer Non-Linear Programming (MINLP) formulation is developed, in which the location of a single UAV-BS and bandwidth allocations to users are jointly determined. The objective is to maximize the total profit without exceeding the backhaul and access capacities. The profit gained from a specific user is assumed to be a piecewise-linear function of the provided data rate level, where higher data rate levels would yield higher profit. Due to high complexity of the MINLP, we propose an efficient heuristic algorithm with lower computational complexity. We show that, when the UAV-BS location is determined, the resource allocation problem can be reduced to a Multidimensional Binary Knapsack Problem (MBKP), which can be solved in pseudo-polynomial time. To exploit this structure, the optimal bandwidth allocations are determined by solving several MBKPs in a search algorithm. We test the performance of our algorithm with two heuristics and with the MINLP model solved by a commercial solver. Our numerical results show that the proposed algorithm outperforms the alternative solution approaches and would be a promising tool to improve the total network profit.Doctoral Thesis Yiyecek içecek sektörü için çok ürünlü, çok aşamalı üretim planlamasına yönelik model ve karar destek sistemi önerisi(2016) Tirkeş, Güzin; Çelebi, Neşe; Koyuncu, MuratGıda ve içecek endüstrisinde; üretim planlama kararı güvenilir bir talep tahminine bağlıdır. Bu üretim alanlarında -özellikle hammaddelerin bozulabilir olduğu düşünüldüğünde- taleplerin zamanlamasını tahmin etmek; üretimi planlamak ve müşteri gereksinimlerini karşılamak için çok önemlidir. Literatürde gıda ve içecek endüstrisinde talep tahmini yapmak için, otoregresif hareketli ortalama (ARMA), otoregresif entegre hareketli ortalama (ARIMA), doğrusal olmayan ARMA modelleri, Holt-Winters metodları, yapay sinir ağları (ANN), genetik algoritmalar gibi çeşitli istatistiksel modellerin denendiği görülmektedir. Yapılacak tahminler için kullanılacak model verilerin karakteristiğine -'eğilim' veya 'mevsimsellik' özelliklerine- bağlıdır. Bu çalışmada 'gerçel zamanlı, çok aşamalı ve çok hatlı' bir üretim sürdürürken, hem toptan hem de perakende satış yapan bir reçel-şerbet üretim tesisi ele alınmaktadır. Tesisin; kapasite sınırlamaları ve taleplerin belirsizliği gibi sorunların varlığında oluşan üretim zamanlaması problemini çözebilmek için 'zaman serileri analizi' temelli bir talep tahmini yaklaşım modeli kurulmuştur ve bu çalışmada bu model tanıtılmaktadır. Uzun dönem talep tahmini için kullanılan 'zaman serileri modeli işletmenin iki yıllık satış verilerinden elde edilen aylık satış bilgilerinden oluşturulmuştur. Modelde Holt ve Winters'ın üçlü üstel düzleştirme ve mevsimsel düzeltme metotları kullanılarak 2015 yılı için talep tahmini yapılmıştır. Uygulama, gıda ve içecek sektöründe mevsimsel belirsizlikleri ele alabilen ilk çalışmalardan biridir. Modelin tutarlılığında hata ölçütü olarak ortalama mutlak yüzdesel hata (MAPE) kriteri ele alınmıştır. Talep tahmin modelini kurduktan sonra, envanter planlama modülünü de içeren, üretim planlama ve zamanlama modeli olarak karışık tam sayılı programlama modeli kullanılmıştır. Geliştirilen modelin 'belirsizlik' içeren durumlara da kolaylıkla uyum gösterebilir olması, modeli hem şu anki problemin çözümü hem de gelecekteki çalışmalar için en uygun seçenek kılmaktadır. Çalışmanın son kısmında, uç noktalara varan değişken taleplerin olduğu durumlarda kullanıcılara yardımcı olabilecek bir karar destek sistemi önerilmiştir.
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