Nazire Nurdan ÇAKIR

Makale/Derleme | 2019 | Clin Oral Investig.

Objectives The aim of this study was to evaluate the 24-month clinical performance of universal adhesives on the restoration success of Class I carious lesions. Materials and methods Five different universal adhesives (Gluma Bond Universal (GU), Clearfil Universal (CU), Prime&Bond Elect Universal (PU), All bond Universal (AU), and Single Bond Universal (SU)) were used in the self-etch and etch-and-rinse modes in 42 patients. The study was conducted with 10 groups, with 20 restorations in each group. The restorations were evaluated at baseline and during a 24-month recall using World Dental Federation (FDI) and the US Public Health S . . .ervice (USPHS) criteria. The changes in the parameters were analyzed using the chi-square test. Results At the end of 24 months, there was no loss of restoration in any group. According to the USPHS, there was no difference in the baseline and 24-month clinical behavior of the restorations (P ˃ 0.05). However, according to the FDI, when adhesives were used in the self-etch mode, three adhesives (GU, SU, PU) showed marginal incompatibility, and one adhesive showed (GU) marginal discoloration between baseline and the 24-month follow-up evaluation (P Daha fazlası Daha az

Oğuzhan Ahmet ARIK

Makale/Derleme | 2021 | Operational Research An International Journal

Additive manufacturing (AM) is a candidate to be one of the future general-purpose technologies. AM is called with 3D printing, Rapid Prototyping, Direct Digital Manufacturing, layered manufacturing, and/or additive manufacturing. Today, AM is a tool for producing customized small products with small lot sizes. Tomorrow, it will be possible for AM to enter every home and to be used for general purposes. The literature about AM has focused mainly on the technology to decrease the cost of AM, to increase the speed of AM machines, and to increase the common availability of those machines. There are so few papers investigating AM machin . . .es in view of scheduling problems. This paper considers a single AM machine that produces multiple parts in batches and then these parts are assembled to produce desired goods. Most AM machines have limitations because of the area of the machine tray and the height of the machine. Therefore, products are separated into small parts considering the area and height of the machine. Then, these separated small parts are assembled to produce the desired goods. In view of scheduling problems, the proposed problem includes single machine batch scheduling and assembly operations. In this paper, we propose a mixed-integer programming (MIP) model and a fast heuristic method with a simple local search mechanism for the problem. We investigate two cases for the same problem. In the frst, we consider only the one-dimensional assignment of parts to baches and we just design our solution approaches to assign parts to the batch, if the total area of parts is less than or equal to the machine tray’s area. In the second, we modify our solution approaches to consider parts’ lengths and widths while assigning parts to batches in a 2D assignment. In the end, we compare the proposed heuristic with the proposed MIP by using some test problems within time limits for all cases. Experimental results show that the proposed heuristic provides promising results Daha fazlası Daha az

Oğuzhan Ahmet ARIK

Makale/Derleme | 2021 | Neural Computing and Applications

The permutation flow shop scheduling problem has been investigated by researchers for more than 40 years due to its complexity and lots of real-life examples of the problem. Many exact or approximate solution approaches have been presented for the problem. Among solution approaches in the literature, iterated greedy algorithm and its variants are the most effective solution methods for the problem. This paper proposes a hybrid solution algorithm that uses the best components such as local search operators and destruction/construction operators of the variants of iterated greedy algorithm in an artificial bee colony algorithm. An ANO . . .VA is made for determining the most proper components of iterated greedy algorithm. Then, these components are combined with artificial bee colony algorithm. Furthermore, a design of experiment is made for determining the best parameter setting for the proposed hybrid artificial bee colony. The experimental results of the proposed algorithm compared with variants of iterated greedy algorithms in the literature show that the proposed algorithm produces better solutions that deviate less from the optimum or lower-bound solutions for permutation flow shop scheduling problems with the makespan performance criterion Daha fazlası Daha az

Oğuzhan Ahmet ARIK

Makale/Derleme | 2021 | SOFT COMPUTING

This paper investigates permutation flow shop scheduling (PFSS) problems under the effects of position-dependent learning and linear deterioration. In a PFSS problem, there are n jobs and m machines in series. Jobs are separated into operations on m different machines in series, and jobs have to follow the same machine order with the same sequence. The PFSS problem under the effects of learning and deterioration is introduced with a mixed-integer nonlinear programming model. The time requirement for solving large-scale problems type of PFSS problem is exceedingly high. Therefore, wellknown metaheuristic methods for the PFSS problem . . .without learning and deterioration effects such as iterated greedy algorithms and discrete differential evolution algorithm are adapted for the problem with learning and deterioration effects in order to find a faster and near-optimal or optimal solution for the problem. Furthermore, this paper proposes a hybrid solution algorithm that is called population-based Tabu search algorithm (TSPOP) with evolutionary strategies such as crossover and mutation. The search algorithm is built on the basic structure of Tabu search and it searches for the best candidate from a solution population instead of improving the current best candidate at each iteration. Furthermore, the performances of these methods in view of solution quality are discussed in this paper by using test problems for 20, 50, and 100 jobs with 5, 10, 20 machines. Experimental results show that the proposed TSPOP algorithm outperforms the other existing algorithms in view of solution quality Daha fazlası Daha az

Oğuzhan Ahmet ARIK

Makale/Derleme | 2021 | International Journal of Applied Metaheuristic Computing

This paper investigates parallel machine scheduling problems where the objectives are to minimize total completion times under effects of learning and deterioration. The investigated problem is in NP-hard class and solution time for finding optimal solution is extremely high. The authors suggested a genetic algorithm, a well-known and strong metaheuristic algorithm, for the problem and we generated some test problems with learning and deterioration effects. The proposed genetic algorithm is compared with another existing metaheuristic for the problem. Experimental results show that the proposed genetic algorithm yield good solutions . . . in very short execution times and outperforms the existing metaheuristic for the problem Daha fazlası Daha az

Gülçin CANBULUT | Erkan KÖSE | Oğuzhan Ahmet ARIK

Makale/Derleme | 2021 | Public Transportation

The success of businesses today is largely dependent on their ability to find solutions to complex problems they encounter. Vehicle selection, which requires considering many objective and subjective criteria, is at the top of these problems. The tramway selection problem of a company operating in the public transport sector in Turkey is discussed in this study. The company wants to increase passenger carrying capacity and renew its vehicle fleet. For this purpose, it has to choose from eight alternative vehicles with different superior features. Considering the high costs that may arise from wrong selection, it becomes clear how im . . .portant it is to use the right method to solve the problem. In this study, the evaluation criteria were determined by taking the opinions of experts first. Then, weights were assigned to the criteria using the Analytical Hierarchy Process (AHP). In the last stage, the best alternative has been tried to be determined by using grey relationship analysis (GRA). It is common to use more than one method to test the reliability of the results in solving multi-criteria decision-making (MCDM) problems. In this study, multi-objective optimization, based on ratio analysis (MOORA), which is one of the most preferred methods to solve MCDM problems, was used to test the accuracy of the results. Although various MCDM methods are used in the literature to solve similar problems, the use of grey relationship analysis has not been encountered. With this aspect, this study has expanded the application of grey theory and made an important contribution to the literature. Another important contribution of the study is that the evaluation criteria for the tramway selection problem have been determined with the help of experts. Finally, this study presents a scientific approach to the solution of a complex real-life problem Daha fazlası Daha az

Oğuzhan Ahmet ARIK

Makale/Derleme | 2022 | Gazi University Journal of Science and Technology

In this paper, permutation flow shop scheduling problems (PFSS) are investigated with a genetic algorithm. PFSS problem is a special type of flow shop scheduling problem. In a PFSS problem, there are n jobs to be processed on m machines in series. Each job has to follow the same machine order and each machine must process jobs in the same job order. The most common performance criterion in the literature is the makespan for permutation scheduling problems. In this paper, a genetic algorithm is applied to minimize the makespan. Taillard’s instances including 20, 50, and 100 jobs with 5, 10, and 20 machines are used to define the effi . . .ciency of the proposed GA by considering lower bounds or optimal makespan values of instances. Furthermore, a sensitivity analysis is made for the parameters of the proposed GA and the sensitivity analysis shows that crossover probability does not affect solution quality and elapsed time. Supplementary to the parameter tuning of the proposed GA, we compare our GA with an existing GA in the literature for PFSS problems and our experimental study reveals that our proposed and well-tuned GA outperforms the existing GA for PFSS problems when the objective is to minimize the makespan Daha fazlası Daha az