Yazılım Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/2147

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Citation - WoS: 182
Citation - Scopus: 243
A comprehensive survey on recent metaheuristics for feature selection
(Elsevier, 2022) Dokeroglu, Tansel; Deniz, Ayca; Kiziloz, Hakan Ezgi; 234173
Feature selection has become an indispensable machine learning process for data preprocessing due to the ever-increasing sizes in actual data. There have been many solution methods proposed for feature selection since the 1970s. For the last two decades, we have witnessed the superiority of metaheuristic feature selection algorithms, and tens of new ones are being proposed every year. This survey focuses on the most outstanding recent metaheuristic feature selection algorithms of the last two decades in terms of their performance in exploration/exploitation operators, selection methods, transfer functions, fitness value evaluations, and parameter setting techniques. Current challenges of the metaheuristic feature selection algorithms and possible future research topics are examined and brought to the attention of the researchers as well.
Citation - WoS: 11
Citation - Scopus: 11
A Constraint Programming Approach To A Real-World Workforce Scheduling Problem For Multi-Manned Assembly Lines With Sequence-Dependent Setup Times
(Taylor & Francis Ltd, 2024) Güner, Funda; Guner, Funda; Satır, Benhür; Gorur, Abdul K.; Satir, Benhur; Kandiller, Levent; Kandiller, Levent; Drake, John H.; 54700; Çankaya Meslek Yüksekokulu; Endüstri Mühendisliği
For over five decades, researchers have presented various assembly line problems. Recently, assembly lines with multiple workers at each workstation have become very common in the literature. These lines are often found in the manufacturing of large vehicles, where workers at a workstation may perform their assigned tasks at the same time. Most research on multi-manned assembly lines focuses on balancing tasks and workers among workstations and scheduling tasks for workers. This study, however, concentrates on assigning tasks to workers already assigned to a specific workstation, rather than balancing the entire line. The problem was identified through an industrial case study at a large vehicle manufacturing company. The study presents two methods, one using mixed integer linear programming and the other using constraint programming, to minimise the number of workers required on a multi-manned assembly line with sequence-dependent setup times. The results of the computational experiments indicate that the constraint programming method performs better than the mixed integer linear programming method on several modified benchmark instances from the literature. The constraint programming model is also tested on the real-world scenario of our industrial case study and leads to significant improvements in the productivity of the workstations.
Citation - WoS: 3
Citation - Scopus: 4
A new robust Harris Hawk optimization algorithm for large quadratic assignment problems
(Springer London Ltd, 2023) Dokeroglu, Tansel; Ozdemir, Yavuz Selim; 234173
Harris Hawk optimization (HHO) is a new robust metaheuristic algorithm proposed for the solution of large intractable combinatorial optimization problems. The hawks are cooperative birds and use many intelligent hunting techniques. This study proposes new HHO algorithms for solving the well-known quadratic assignment problem (QAP). Large instances of the QAP have not been solved exactly yet. We implement HHO algorithms with robust tabu search (HHO-RTS) and introduce new operators that simulate the actions of hawks. We also developed an island parallel version of the HHO-RTS algorithm using the message passing interface. We verify the performance of our proposed algorithms on the QAPLIB benchmark library. One hundred and twenty-five of 135 problems are solved optimally, and the average deviation of all the problems is observed to be 0.020%. The HHO-RTS algorithm is a robust algorithm compared to recent studies in the literature.
Citation - WoS: 6
Citation - Scopus: 7
An island parallel Harris hawks optimization algorithm
(Springer London Ltd, 2022) Dokeroglu, Tansel; Sevinc, Ender; 234173
The Harris hawk optimization (HHO) is an impressive optimization algorithm that makes use of unique mathematical approaches. This study proposes an island parallel HHO (IP-HHO) version of the algorithm for optimizing continuous multi-dimensional problems for the first time in the literature. To evaluate the performance of the IP-HHO, thirteen unimodal and multimodal benchmark problems with different dimensions (30, 100, 500, and 1000) are evaluated. The implementation of this novel algorithm took into account the investigation, exploitation, and avoidance of local optima issues effectively. Parallel computation provides a multi-swarm environment for thousands of hawks simultaneously. On all issue cases, we were able to enhance the performance of the sequential version of the HHO algorithm. As the number of processors increases, the suggested IP-HHO method enhances its performance while retaining scalability and improving its computation speed. The IP-HHO method outperforms the other state-of-the-art metaheuristic algorithms on average as the size of the dimensions grows.
Citation - WoS: 8
Citation - Scopus: 7
Assessment of improvement of the IRI model for foF2 variability over three latitudes in different hemispheres during low and high solar activities
(Pergamon-elsevier Science Ltd, 2021) Timocin, Erdinc; Temucin, Huseyin; Inyurt, Samed; Shah, Munawar; Jamjareegulgarn, Punyawi; 182651
This paper discusses the diurnal and seasonal variations of the F2 layer critical frequency (foF2) and the improvement of performance of the IRI-2016 model in predicting foF2 over three latitudes in different hemispheres during low and high solar activities. We extracted the foF2 data from six ionosonde stations which are Manila (14.7 degrees N, 121.1 degrees E), Yamagawa (31.2 degrees N, 130.6 degrees E), Yakutsk (62.0 degrees N,129.6 degrees E), Townsville (19.6 degrees S, 146.8 degrees E), Hobart (42.9 degrees S, 147.3 degrees E) and Terre Adelie (66.6 degrees S, 140.0 degrees E). The data of both low solar activity (LSA) period and high solar activity (HSA) periods were divided into three seasons as Northern Summer (May, June, July and August), Equinoxes (March, April, September and October) and Northern Winter (November, December, January and February). The present study showed that the IRI-2016 performance is strongly dependent on the solar activity, latitude, season, local time and hemisphere. For both hemispheres, the foF2 values at low latitude station are larger than those at middle latitude station, whereas the foF2 values at middle latitude station are larger than those at high latitude station. The agreement between IRI2016-modelled foF2 and foF2 measurements on all stations selected in the northern hemisphere is best for North Summer and worst for North Winter. For northern hemisphere, the values of relative deviations during both solar activities are largest in high latitudes and smallest in middle latitudes. As for southern hemisphere, the values of relative deviations during LSA are largest in middle latitudes and smallest in high latitudes, whereas the values of relative deviations during HSA are largest in low latitudes and smallest in high latitudes. It is thought that the relative deviations in the observed foF2 values are caused by solar activity that strongly alter chemical and electromagnetic processes in the ionosphere. These results are important for future improvements depending on solar activity and seasons in the IRI model for foF2 values over three latitudes in different hemispheres.
Citation - WoS: 20
Citation - Scopus: 29
Creating consensus group using online learning based reputation in blockchain networks
(Elsevier, 2019) Bugday, Ahmet; Sever, Hayri; Ozsoy, Adnan; Oztaner, Serdar Murat; Sever, Hayri; 11916; Bilgisayar Mühendisliği
One of the biggest challenges to blockchain technology is the scalability problem. The choice of consensus algorithm is critical to the practical solution of the scalability problem. To increase scalability, Byzantine Fault Tolerance (BFT) based methods have been most widely applied. This study proposes a new model instead of Proof of Work (PoW) for forming the consensus group that allows the use of BFT based methods in the public blockchain network. The proposed model uses the adaptive hedge method, which is a decision-theoretic online learning algorithm (Qi et al., 2016). The reputation value is calculated for the nodes that want to participate in the consensus committee, and nodes with high reputation values are selected for the consensus committee to reduce the chances of the nodes in the consensus committee being harmful. Since the study focuses on the formation of the consensus group, a simulated blockchain network is used to test the proposed model more effectively. Test results indicate that the proposed model, which is a new approach in the literature making use of machine learning for the construction of consensus committee, successfully selects the node with the higher reputation for the consensus group. (C) 2019 Elsevier B.V. All rights reserved.
Citation - WoS: 19
Citation - Scopus: 27
Hyper-heuristics: A survey and taxonomy
(Pergamon-elsevier Science Ltd, 2024) Dokeroglu, Tansel; Dökeroğlu, Tansel; Kucukyilmaz, Tayfun; Talbi, El-Ghazali; 234173; Yazılım Mühendisliği
Hyper-heuristics are search techniques for selecting, generating, and sequencing (meta)-heuristics to solve challenging optimization problems. They differ from traditional (meta)-heuristics methods, which primarily employ search space-based optimization strategies. Due to the remarkable performance of hyper-heuristics in multi-objective and machine learning-based optimization, there has been an increasing interest in this field. With a fresh perspective, our work extends the current taxonomy and presents an overview of the most significant hyper-heuristic studies of the last two decades. Four categories under which we analyze hyperheuristics are selection hyper-heuristics (including machine learning techniques), low-level heuristics, target optimization problems, and parallel hyper-heuristics. Future research prospects, trends, and prospective fields of study are also explored.
Citation - WoS: 19
Citation - Scopus: 22
Investigation of equatorial plasma bubble irregularities under different geomagnetic conditions during the equinoxes and the occurrence of plasma bubble suppression
(Pergamon-elsevier Science Ltd, 2020) Timocin, Erdinc; Inyurt, Samed; Temucin, Huseyin; Ansari, Kutubuddin; Jamjareegulgarn, Punyawi; 182651
In this study, we investigated the behavior of equatorial plasma bubble irregularities under different geomagnetic conditions during March 2015 and September 2017. It was used Total Electron Content (TEC) data obtained from SGOC (6,89 degrees N, 79,87 degrees E), IISC (12,94 degrees N, 77,57 degrees E) and HYDE (17,40 degrees N, 78,50 degrees E) receiver stations which located between the trough and the crest of the equatorial ionization anomaly (EIA). We used the Rate of TEC change (ROT) and Rate of TEC change index (ROTI) to represent plasma bubbles irregularities. These indices are a well proxy for the ionospheric fluctuations and can be used to describe features of plasma bubbles irregularities. The equatorial plasma bubble irregularities for all stations were observed between 13 UT and 20 UT (during postsunset period) during equinoxes. The intensity level of ROTI during postsunset periods was greater than 1 TECU min(-1). Also, the values of mean ROTI (ROTIave) between 13 UT and 20 UT have values greater than 0,4 TECU min(-1) while the values of ROTIave at the other hours have values less than 0,4 TECU min(-1). The geomagnetic activity has a significant effect on the occurrence of equatorial plasma bubbles irregularities. The occurrence rate of equatorial plasma bubble irregularities observed during postsunset hours increased as geomagnetic activity increases. It also was observed that the main phases of geomagnetic storms have the triggering effect of storms on equatorial plasma bubble irregularities observed at postsunset hours while the recovery phases of geomagnetic storms have the suppression effect of storms on equatorial plasma bubble irregularities. Asymmetry between two equinoxes was observed. The occurrence rate of equatorial plasma bubble irregularities in the March equinox was much larger than that of the September equinox. The occurrence probability of equatorial plasma bubbles for March Equinox was maximum with 45,1% at 17 UT while the occurrence probability of equatorial plasma bubbles for September Equinox was maximum with 11,5% at 16 UT. The enhancements and reductions in the latitudinal gradient of VTEC show similar behaviors with the occurrence of equatorial plasma irregularities. The EIA during postsunset hours contributes significantly to the occurrence of equatorial plasma bubbles irregularities.

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