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Full-Text Articles in Physical Sciences and Mathematics
Task Offloading And Resource Allocation Based On Dl-Ga In Mobile Edge Computing, Hang Gu, Minjuan Zhang, Wenzao Li, Yuwen Pan
Task Offloading And Resource Allocation Based On Dl-Ga In Mobile Edge Computing, Hang Gu, Minjuan Zhang, Wenzao Li, Yuwen Pan
Turkish Journal of Electrical Engineering and Computer Sciences
With the rapid development of 5G and the Internet of Things (IoT), the traditional cloud computing architecture struggle to support the booming computation-intensive and latency-sensitive applications. Mobile edge computing (MEC) has emerged as a solution which enables abundant IoT tasks to be offloaded to edge services. However, task offloading and resource allocation remain challenges in MEC framework. In this paper, we add the total number of offloaded tasks to the optimization objective and apply algorithm called Deep Learning Trained by Genetic Algorithm (DL-GA) to maximize the value function, which is defined as a weighted sum of energy consumption, latency, and …
A New Hybrid Genetic Algorithm For Protein Structure Prediction On The 2dtriangular Lattice, Bouroubi Sadek, Nabil Boumedine
A New Hybrid Genetic Algorithm For Protein Structure Prediction On The 2dtriangular Lattice, Bouroubi Sadek, Nabil Boumedine
Turkish Journal of Electrical Engineering and Computer Sciences
The flawless functioning of the protein is essentially related to its three-dimensional structure. Therefore,predicting protein structure from its amino acid sequence is a fundamental problem that draws researchers' attentionin many areas. The protein structure prediction problem (PSP) can be formulated as a combinatorial optimization problem based on simplified lattice models such as the hydrophobic-polar model. In this paper, we propose a new hybridalgorithm that combines three different known heuristic algorithms: the genetic algorithm, the tabu search strategy,and the local search algorithm to solve the PSP problem. Regarding the evaluation of the proposed approach, wepresent an experimental study, where we consider …
Analysis Of Shielding Effectiveness By Optimizing Aperture Dimensions Of Arectangular Enclosure With Genetic Algorithm, Sunay Güler, Si̇bel Yeni̇kaya
Analysis Of Shielding Effectiveness By Optimizing Aperture Dimensions Of Arectangular Enclosure With Genetic Algorithm, Sunay Güler, Si̇bel Yeni̇kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Electromagnetic compatibility (EMC) has now become a substantial challenge more than any other time sincethe number of electric vehicles (EV) increased rapidly. The electric driving system in an EV consists of power electroniccomponents supplied by high voltage battery source. They are both source and victim of potential electromagneticinterference (EMI) since fast switching process occurs inside them. Electromagnetic shielding provides a significantprotection against EMI for any electrical and electronic components inside the vehicle. In this paper, analysis of shieldingeffectiveness (SE) by optimizing aperture dimensions of a rectangular enclosure is investigated. Realistic dimensions of theshielding enclosure of an inverter component are employed. …
Adaptation Of Metaheuristic Algorithms To Improve Training Performance Of Aneszsl Model, Şi̇fa Özsari, Mehmet Serdar Güzel, Gazi̇ Erkan Bostanci, Ayhan Aydin
Adaptation Of Metaheuristic Algorithms To Improve Training Performance Of Aneszsl Model, Şi̇fa Özsari, Mehmet Serdar Güzel, Gazi̇ Erkan Bostanci, Ayhan Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Zero-shot learning (ZSL) is a recent promising learning approach that is similar to human vision systems. ZSL essentially allows machines to categorize objects without requiring labeled training data. In principle, ZSL proposes a novel recognition model by specifying merely the attributes of the category. Recently, several sophisticated approaches have been introduced to address the challenges regarding this problem. Embarrassingly simple approach to zeroshot learning (ESZSL) is one of the critical of those approaches that basically proposes a simple but efficient linear code solution. However, the performance of the ESZSL model mainly depends on parameter selection. Metaheuristic algorithms are considered as …
Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n
Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
Software quality assurance is one of the crucial factors for the success of software projects. Bug fixing has an essential role in software quality assurance, and bug localization (BL) is the first step of this process. BL is difficult and time-consuming since the developers should understand the flow, coding structure, and the logic of the program. Information retrieval-based bug localization (IRBL) uses the information of bug reports and source code to locate the section of code in which the bug occurs. It is difficult to apply other tools because of the diversity of software development languages, design patterns, and development …
Gene Expression Data Classification Using Genetic Algorithm-Basedfeature Selection, Öznur Si̇nem Sönmez, Mustafa Dağteki̇n, Tolga Ensari̇
Gene Expression Data Classification Using Genetic Algorithm-Basedfeature Selection, Öznur Si̇nem Sönmez, Mustafa Dağteki̇n, Tolga Ensari̇
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, hybrid methods are proposed for feature selection and classification of gene expression datasets. In the proposed genetic algorithm/support vector machine (GA-SVM) and genetic algorithm/k nearest neighbor (GA-KNN) hybrid methods, genetic algorithm is improved using Pearson's correlation coefficient, Relief-F, or mutual information. Crossover and selection operations of the genetic algorithm are specialized. Eight different gene expression datasets are used for classification process. The classification performances of the proposed methods are compared with the traditional GA-KNN and GA-SVM wrapper methods and other studies in the literature. Classification results demonstrate that higher accuracy rates are obtained with the proposed methods …
A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale
A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale
Turkish Journal of Electrical Engineering and Computer Sciences
Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …
A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh
A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh
Turkish Journal of Electrical Engineering and Computer Sciences
One of the critical factors that make a search engine fast and accurate is a concise and duplicate free index. In order to remove duplicate and near-duplicate (DND) documents from the index, a search engine needs a swift and reliable DND text document detection system. Traditional approaches to this problem, such as brute force comparisons or simple hash-based algorithms, are not suitable as they are not scalable and are not capable of detecting near-duplicate documents effectively. In this paper, a new signature-based approach to text similarity detection is introduced, which is fast, scalable, and reliable and needs less storage space. …
Chemical Disease Relation Extraction Task Using Genetic Algorithm With Two Novelvoting Methods For Classifier Subset Selection, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş
Chemical Disease Relation Extraction Task Using Genetic Algorithm With Two Novelvoting Methods For Classifier Subset Selection, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş
Turkish Journal of Electrical Engineering and Computer Sciences
Biomedical relation extraction is an important preliminary step for knowledge discovery in the biomedical domain. This paper proposes a multiple classifier system (MCS) for the extraction of chemical-induced disease relations. A genetic algorithm (GA) is employed to select classifier ensembles from a pool of base classifiers. Moreover, the voting method used for combining the members of each of the ensembles is also selected during evolution in the GA framework. The performances of the MCSs are determined by the algorithms used for selecting the classifiers, the diversity among the selected classifiers, and the voting method used in the classifier combination. The …
A Ga-Based Adaptive Mechanism For Sensorless Vector Control Of Induction Motor Drives For Urban Electric Vehicles, Asma Boulmane, Youssef Zidani, Driss Belkhayat, Marouane Bouchouirbat
A Ga-Based Adaptive Mechanism For Sensorless Vector Control Of Induction Motor Drives For Urban Electric Vehicles, Asma Boulmane, Youssef Zidani, Driss Belkhayat, Marouane Bouchouirbat
Turkish Journal of Electrical Engineering and Computer Sciences
Induction motors are more attractive to car manufacturers because they are more robust and more cost effective to maintain in comparison with other types of electric machines. The evolution of their control makes them more efficient and less expensive. However, a new control technique known as sensorless control is being used to simplify the implementation of electric machines in electric vehicles. This technique involves replacing the flux and speed sensors with an observer. The estimation of these elements is based on the measurement of currents and voltages. The main purpose of the present study is to design a novel robust …
An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi
An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi
Turkish Journal of Electrical Engineering and Computer Sciences
A genetic algorithm (GA) is not a good option for finding solutions around in neighborhoods. The current study applies a memetic algorithm (MA) with a proposed local search to the mutation operator of a genetic algorithm in order to solve the traveling salesman problem (TSP). The proposed memetic algorithm uses swap, reversion and insertion operations to make changes in the solution. In the basic GA, unlike in the real world, the relationship between generations has not been considered. This gap is resolved using the proposed complex network to allow selection among possible solutions. The degree measure has been used for …
Fuzzy Genetic Based Dynamic Spectrum Allocation (Fgdsa) Approach For Cognitive Radio Sensor Networks, Ganesan Rajesh, Xavier Mercilin Raajini, Kulandairaj Martin Sagayam, Bharat Bhushan, Utku Kose
Fuzzy Genetic Based Dynamic Spectrum Allocation (Fgdsa) Approach For Cognitive Radio Sensor Networks, Ganesan Rajesh, Xavier Mercilin Raajini, Kulandairaj Martin Sagayam, Bharat Bhushan, Utku Kose
Turkish Journal of Electrical Engineering and Computer Sciences
Cognitive Radio Sensor Network (CRSN) is known as a distributed network of wireless cognitive radio sensor nodes. Such system senses an event signal and ensures collaborative dynamic communication processes over the spectrum bands. Here, the concept of Dynamic Spectrum Access (DSA) denes the method of reaching progressively to the unused range of spectrum band. As among the essential CRSN user types, the Primary User (PU) has the license to access the spectrum band. On the other hand, the Secondary User (SU) tries to access the unused spectrum eciently, by not disturbing the PU. Considering that issue, this study introduces a …
Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh
Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an optimized bilevel brain tumor diagnostic system for identifying the tumor type at the first level and grade of the identified tumor at the second level is proposed using genetic algorithm, decision tree, and fuzzy rule-based approach. The dataset is composed of axial MRI of brain tumor types and grades. From the images, various features such as first and second order statistical and textural features are extracted (26 features). In the first level, tumor type classification was done using decision tree constructed with all features. Further evolutionary computing using genetic algorithms (GA) was applied to select the …
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Turkish Journal of Electrical Engineering and Computer Sciences
The development and improvement of control techniques has attracted many researchers for many years. Especially in the controller design of complex and nonlinear systems, various methods have been proposed to determine the ideal control parameters. One of the most common and effective of these methods is determining the controller parameters with optimization algorithms.In this study, LQR controller design was implemented for position control of the double inverted pendulum system on a cart. First of all, the equations of motion of the inverted pendulum system were obtained by using Lagrange formulation. These equations were linearized by Taylor series expansion around the …
Transmission Expansion Planning Based On A Hybrid Genetic Algorithm Approachunder Uncertainty, Ercan Şenyi̇ği̇t, Selçuk Mutlu, Bi̇lal Babayi̇ği̇t
Transmission Expansion Planning Based On A Hybrid Genetic Algorithm Approachunder Uncertainty, Ercan Şenyi̇ği̇t, Selçuk Mutlu, Bi̇lal Babayi̇ği̇t
Turkish Journal of Electrical Engineering and Computer Sciences
Transmission expansion planning (TEP) is one of the key decisions in power systems. Its impact on the system?s operation is excessive and long-lived. The aim of TEP is to determine new transmission lines effectively for a current transmission grid to fulfill the model objectives. However, to obtain a solution, especially under uncertainty, is extremely difficult due to the nonlinear mixed-integer structure of the TEP problem. In this paper, first genetic algorithm (GA) approaches for TEP are reviewed in the literature and then a new hybrid GA with linear modeling is proposed. The proposed GA method has a flexible structure and …
Automatic Prostate Segmentation Using Multiobjective Active Appearance Model In Mr Images, Ahad Salimi, Mohammad Ali Pourmina, Mohamma-Shahram Moien
Automatic Prostate Segmentation Using Multiobjective Active Appearance Model In Mr Images, Ahad Salimi, Mohammad Ali Pourmina, Mohamma-Shahram Moien
Turkish Journal of Electrical Engineering and Computer Sciences
Prostate cancer is the second largest cause of mortality among men. Prostate segmentation, i.e. the precise determination of the prostate region in magnetic resonance imaging (MRI), is generally used for prostate volume measurement, which can be used as a potential prostate cancer indicator. This paper presents a new fully automatic statistical model called the multiobjective active appearance model (MOAAM) for prostate segmentation in MR images. First, in the training stage, the appearance model, including the shape and texture model, is developed by applying principal component analysis to the training images, already outlined by a physician. Then noise and roughness are …
Gacnn Sleeptunenet: A Genetic Algorithm Designing The Convolutional Neural Network Architecture For Optimal Classification Of Sleep Stages From A Single Eeg Channel, Shahnawaz Qureshi, Seppo Karilla, Sirirut Vanichayobon
Gacnn Sleeptunenet: A Genetic Algorithm Designing The Convolutional Neural Network Architecture For Optimal Classification Of Sleep Stages From A Single Eeg Channel, Shahnawaz Qureshi, Seppo Karilla, Sirirut Vanichayobon
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a method for designing--by a genetic algorithm, without manual intervention--the feature learning architecture for classification of sleep stages from a single EEG channel, when using a convolutional neural network called GACNN SleepTuneNet. Two EEG electrode positions were selected, namely FP2-F4 and FPz-Cz, from two available datasets. Twenty-five generations were involved in diagnosis without hand-crafted features, to learn the architecture for classification of sleep stages based on AASM standard. Based on the results, our model not only achieved the highest classification accuracy, but it also distinguished the sleep stages based on either of the two EEG electrode signals, …
Performance Enhancement Of Photovoltaic System Using Genetic Algorithm- Based Maximum Power Point Tracking, Brammanayagam Nagarani, Jothiswaroopan Nesamony
Performance Enhancement Of Photovoltaic System Using Genetic Algorithm- Based Maximum Power Point Tracking, Brammanayagam Nagarani, Jothiswaroopan Nesamony
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, enormous progress has been made on power generation using photovoltaic (PV) system. Solar power is one of the most promising renewable energy sources that is providing its benefit specifically in rural areas. With the increasing need for solar energy, it becomes necessary to extract maximum power from the PV array. The output power of the solar cells varies directly with the ambient temperature and Irradiation. Therefore, the challenge is to track maximum power from the PV array when environmental factors change. This paper focuses on increasing the efficiency of a PV array by incorporating artificial intelligence techniques. …
Generation Rescheduling Using Multiobjective Bilevel Optimization, Kiran Babu Vakkapatla, Srinivasa Varma Pinni
Generation Rescheduling Using Multiobjective Bilevel Optimization, Kiran Babu Vakkapatla, Srinivasa Varma Pinni
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new multiobjective optimization method that can be used for generation rescheduling in power systems. Generation rescheduling in restructured power systems is performed by the system operator for different operations like congestion management, day-ahead scheduling, and preventive maintenance. The nonlinear nature of the equations involved and the constraints on decision variables pose a challenge to find the global optimum. In order to find the global optimum using a genetic algorithm, a bilevel optimization method is proposed. In the proposed multiobjective optimization method, the objectives are classified as primary and secondary based on their relative importance. The best …
Symbolic Interpretation Of Artificial Neural Networks Using Genetic Algorithms, Dounia Yedjour, Abdelkader Benyettou, Hayat Yedjour
Symbolic Interpretation Of Artificial Neural Networks Using Genetic Algorithms, Dounia Yedjour, Abdelkader Benyettou, Hayat Yedjour
Turkish Journal of Electrical Engineering and Computer Sciences
The knowledge acquired during the learning of artificial neural networks (ANNs) is coded as values in synaptic weights, which makes their interpretations difficult, hence the name of the black box. The aim of this work is to provide a comprehensible interpretation of the ANN's decisions by extracting symbolic rules. We improve the performance of our extraction algorithm by combining the ANN with a genetic algorithm. Misleading rules whose support and confidence values are less than fixed thresholds are removed and, as a result, the comprehensibility is improved. The extracted rules are evaluated and compared with other works. The results show …
Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu
Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu
Turkish Journal of Electrical Engineering and Computer Sciences
Load frequency control (LFC) is an essential aspect of power system dynamics. This paper focuses on the optimization of LFC for a two-area deregulated power system under different scenarios. A recent nature-inspired ower pollination algorithm (FPA), based on the pollination process of plants, is used to tune the proportional integral (PI) controller parameters of LFC for the global minima solution. FPA is compared with a genetic algorithm, particle swarm optimization, and a conventional PI controller. During large load disturbance in the areas, controllers are incapable of reducing frequency deviations and tie-line power oscillations due to the slow response of the …
Multiobjective Aerodynamic Optimization Of A Microscale Ducted Wind Turbineusing A Genetic Algorithm, Emre Alpman
Multiobjective Aerodynamic Optimization Of A Microscale Ducted Wind Turbineusing A Genetic Algorithm, Emre Alpman
Turkish Journal of Electrical Engineering and Computer Sciences
A two-objective aerodynamic optimization of a microscale ducted wind turbine was performed using a genetic algorithm. Two different fitness function pairs were considered for this purpose. In the first alternative the algorithm maximized the power produced while minimizing the drag force at a given wind speed and tip speed ratio. In the second alternative, however, the annual energy production was maximized while minimizing the maximum drag force developed between the cut-in and cut-off wind speeds. Computational uid dynamics solutions performed for selected best designs showed that optimizations performed using the second alternative yielded better turbines, which could produce more power …
An Improved Omthd Technique For An N-Level Cascaded Multilevel Inverter With Adjustable Dc Sources, Hamidreza Toodeji
An Improved Omthd Technique For An N-Level Cascaded Multilevel Inverter With Adjustable Dc Sources, Hamidreza Toodeji
Turkish Journal of Electrical Engineering and Computer Sciences
Optimal minimization of total harmonic distortion (OMTHD) and selective harmonic elimination (SHE) switching techniques are usually employed to reduce generated harmonics of multilevel inverters. In the former technique, the THD of waveform is reduced without elimination of any harmonic order and the latter, in contrast, eliminates selected harmonic orders. In this paper, the harmonic elimination ability of the SHE technique is added to OMTHD and an improved OMTHD technique is proposed for an n-level cascaded multilevel inverter with adjustable DC sources. The main novelty of this switching technique is elimination of some harmonic orders, beside THD minimization. Moreover, optimal DC …
Proton--Proton And Proton--Antiproton Differential Elastic Cross Sections Modeling At High And Ultra-High Energies Using A Hybrid Computing Paradigm, Elsayed Eldahshan
Proton--Proton And Proton--Antiproton Differential Elastic Cross Sections Modeling At High And Ultra-High Energies Using A Hybrid Computing Paradigm, Elsayed Eldahshan
Turkish Journal of Physics
This work presents a hybrid computing technique for modeling the differential elastic cross section of both proton--proton ``pp'' and proton--antiproton ``pp(bar)'' collisions from high to ultra-high energy regions (from 13.9 GeV to 14 TeV) as a function of the center-of-mass energy ``s'' squared and four momentum transfer squared ``t''. We proposed a genetic algorithm (GA) and support vector regression (SVR) hybrid techniques to calculate and predict the ``differential elastic cross section'' of both ``pp'' and ``pp(bar)''. Our proposed GA-SVR hybrid model shows a good match to the available experimental data, as well as predicting the latest and future ``TOTEM'' experiments …
Assessment Of Disordered Voices Based On An Optimized Glottal Source Model, Mounir Boudjerda, Abdellah Kacha
Assessment Of Disordered Voices Based On An Optimized Glottal Source Model, Mounir Boudjerda, Abdellah Kacha
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a method for the assessment of disordered voices is proposed. A feature named mean opening quotient (MOQ) obtained from the glottal source estimation is used as an acoustic cue to summarize the degree of severity of the voice disorder. The analysis method uses the empirical mode decomposition algorithm to estimate the glottal source excitation signal from the speech signal. The logarithm of the magnitude spectrum of the speech signal is decomposed into oscillatory modes, called intrinsic mode functions, that are clustered into two classes, the spectral envelope and the harmonic component. The exploitation of the phase information …
A Modified Genetic Algorithm For A Special Case Of The Generalized Assignment Problem, Murat Dörterler, Ömer Faruk Bay, Mehmet Ali̇ Akcayol
A Modified Genetic Algorithm For A Special Case Of The Generalized Assignment Problem, Murat Dörterler, Ömer Faruk Bay, Mehmet Ali̇ Akcayol
Turkish Journal of Electrical Engineering and Computer Sciences
Many central examinations are performed nationwide in Turkey. These examinations are held simultaneously throughout Turkey. Examinees attempt to arrive at the examination centers at the same time and they encounter problems such as traffic congestion, especially in metropolises. The state of mind that this situation puts them into negatively affects the achievement and future goals of the test takers. Our solution to minimize the negative effects of this issue is to assign the test takers to closest examination centers taking into account the capacities of examination halls nearby. This solution is a special case of the generalized assignment problem (GAP). …
Developing A Model And Software For Energy Efficiency Optimization In The Building Design Process: A Case Study In Turkey, Özgür Bayata, İzzetti̇n Temi̇z
Developing A Model And Software For Energy Efficiency Optimization In The Building Design Process: A Case Study In Turkey, Özgür Bayata, İzzetti̇n Temi̇z
Turkish Journal of Electrical Engineering and Computer Sciences
Buildings are responsible for 40% of the primary energy consumption in the world. Recent studies have revealed that the energy efficiency and environmental impact of buildings are two very important criteria to consider during the process of building design for the future of our world. By considering the initial investment cost and its importance for investors, a problem with three objective functions has emerged with 16 building energy systems and 24 construction material alternatives. The aim of this work is to develop a methodology and software to solve multiobjective building optimization problems. Thus, two different software tools have been developed …
Energy Efficient Multiconstrained Optimization Using Hybrid Aco And Ga In Manet Routing, Nivetha Senthil Kumaran, Asokan Ramasamy
Energy Efficient Multiconstrained Optimization Using Hybrid Aco And Ga In Manet Routing, Nivetha Senthil Kumaran, Asokan Ramasamy
Turkish Journal of Electrical Engineering and Computer Sciences
Nodes in mobile ad hoc networks (MANET) suffer from limited battery power and bandwidth. Particularly for real time multimedia communications through MANET, metrics like residual node energy, bandwidth, and end-to-end delay have major impacts. In MANET, designing a dynamic routing algorithm to satisfy quality of service (QoS) requirements is a challenging task. Additionally, multiconstrained QoS routing aims to optimize multiple QoS metrics while providing required network resources and is an admittedly complex problem. It has been proved to be NP-complete when a combination of additive, concave, and multiplicative metrics are considered. Hence, this problem can be solved using metaheuristic methods …
A Ring Crossover Genetic Algorithm For The Unit Commitment Problem, Syed Basit Ali Bukhari, Aftab Ahmad, Syed Auon Raza, Muhammad Noman Siddique
A Ring Crossover Genetic Algorithm For The Unit Commitment Problem, Syed Basit Ali Bukhari, Aftab Ahmad, Syed Auon Raza, Muhammad Noman Siddique
Turkish Journal of Electrical Engineering and Computer Sciences
The unit commitment problem (UCP) is a nonlinear, mixed-integer, constraint optimization problem and is considered a complex problem in electrical power systems. It is the combination of two interlinked subproblems, namely the generator scheduling problem and the generation allocation problem. In large systems, the UCP turns out to be increasingly complicated due to the large number of possible ON and OFF combinations of units in the power system over a scheduling time horizon. Due to the insufficiency of conventional approaches in handling large systems, numerous metaheuristic techniques are being developed for solving this problem. The genetic algorithm (GA) is one …
Optimal Siting And Sizing Of Rapid Charging Station For Electric Vehicles Considering Bangi City Road Network In Malaysia, Mainul Islam, Hussain Shareef, Azah Mohamed
Optimal Siting And Sizing Of Rapid Charging Station For Electric Vehicles Considering Bangi City Road Network In Malaysia, Mainul Islam, Hussain Shareef, Azah Mohamed
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, electric vehicles (EVs) have been seen as a felicitous option towards a less carbon-intensive road transport. The key issue in this system is recharging the EV batteries before they are exhausted. Thus, charging stations (CSs) should be carefully located to make sure EV users can access a CS within their driving range. Considering geographic information and traffic density, this paper proposes an optimization overture for optimal siting and sizing of a rapid CS (RCS). It aims to minimize the daily total cost (which includes the cost of substation energy loss, traveling cost of EVs to the CS, and investment, …