Person: GÜRSES, DİLDAR
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GÜRSES
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DİLDAR
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Publication Comparison of the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, the salp swarm algorithm for real-world engineering applications(Walter De Gruyter Gmbh, 2021-01-01) Gürses, Dildar; Bureerat, Sujin; Sait, Sadiq M.; Yıldız, Ali Rıza; GÜRSES, DİLDAR; YILDIZ, ALİ RIZA; Mühendislik Fakültesi; Makine Mühendisliği Bölümü; JCN-8328-2023 ; F-7426-2011This paper focuses on a comparision of recent algorithms such as the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, and the salp swarm algorithm. The slime mold algorithm (SMA) is a recent optimization algorithm. In order to strengthen its exploitation and exploration abilities, in this paper, a new hybrid slime mold algorithm-simulated annealing algorithm (HSMA-SA) has been applied to structural engineering design problems. As a result of the rules and practices that have become mandatory for fuel emissions by international organizations and governments, there is increasing interest in the design of vehicles with minimized fuel emissions. Many scientific studies have been conducted on the use of metaheuristic methods for the optimum design of vehicle components, especially for reducing vehicle weight. With the inspiration obtained from the above-mentioned methods, the HSMA-SA has been studied to solve the shape optimization of a design case to prove how the HSMA-SA can be used to solve shape optimization problems. The HSMA-SA provides better results as an arithmetic optimization algorithm than the slime mold optimization algorithm, the marine predators algorithm, and the salp swarm algorithm.Publication Artificial gorilla troops algorithm for the optimization of a fine plate heat exchanger(Walter De Gruyter Gmbh, 2022-09-27) Mehta, Pranav; Patel, Vivek; Sait, Sadiq M.; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Gürses, Dildar; GÜRSES, DİLDAR; Mühendislik Fakültesi; Makina Mühendisliği Ana Bilim Dalı; F-7426-2011; JCN-8328-2023Adaptability of the metaheuristic (MH) algorithms in multidisciplinary platforms confirms its significance and effectiveness for the solution of the constraints problems. In this article, one of the imperative thermal system components-plate fin heat exchangers is economically optimized using the novel artificial gorilla troops optimization algorithms (AGTOAs). The cost optimization challenge of the PFHE includes the initial and running cost that needs to be minimized by optimizing several design variables subjecting to critical boundary conditions. To confirm the performance of the AGTOA, the statistical results obtained were compared with nine benchmark MHs algorithms. It was found that AGTO is a robust optimization algorithm because it was able to fetch the best results for the function with 100% of the success rate compared to the rest of the algorithms. Moreover, considering the superior results obtained from the AGTO, it can be applied to numerous applications of the engineering design optimization.Publication Cheetah optimization algorithm for optimum design of heat exchangers(Walter De Gruyter Gmbh, 2023-06-30) Sait, Sadiq M.; Mehta, Pranav; YILDIZ, ALİ RIZA; Gürses, Dildar; GÜRSES, DİLDAR; Mühendislik Fakültesi; 0000-0002-4796-0581; 0000-0003-1790-6987; F-7426-2011; JCN-8328-2023Thermal system optimization is always a challenging task due to several constraints and critical concepts of thermo-hydraulic aspects. Heat exchangers are one of those devices that are widely adopted in thermal industries for various applications such as cryogenics, heat recovery, and heat transfer applications. According to the flow configurations and enhancement of fins, the heat exchangers are classified as plate-fin heat exchangers, shell and tube heat exchangers, and tube-fin heat exchangers. This article addresses the economic optimization challenge of plate-fin heat exchangers using cheetah optimization (CO) algorithm. The design variables were optimized using the CO algorithm, and statistical results were compared with eight well-established algorithms. The study revealed that the cheetah algorithm is prominent in terms of realizing minimizing the overall cost of the plate-fin heat exchanger with a 100 % of success rate. Furthermore, the study suggests adopting the cheetah optimizer for solving optimization challenges in different fields.Publication African vultures optimization algorithm for optimization of shell and tube heat exchangers(Walter De Gruyter Gmbh, 2022-08-26) Mehta, Pranav; Sait, Sadiq M.; Gürses, Dildar; GÜRSES, DİLDAR; Yıldız, Ali Riza; YILDIZ, ALİ RIZA; Mühendislik Fakültesi; 0000-0002-4796-0581; 0000-0003-1790-6987; F-7426-2011Nature-inspired optimization algorithms named meta-heuristics are found to be versatile in engineering design fields. Their adaptability is also used in various areas of the Internet of things, structural design, and thermal system design. With the very rapid progress in industrial modernization, waste heat recovery from the power generating and thermal engineering organization is an imperative key point to reduce the emission and support the government norms. However, the heat exchanger is the component applied in various heat recovery processes. Out of the available designs, shell and tube heat exchangers (SHTHEs) are the most commonly adopted for the heat recovery process. Hence, cost minimization is the major aspect while designing the heat exchanger confirming various constraints and optimized design variables. In this study, cost minimization of the SHTHE is performed by applying a novel metaheuristic algorithm which is the African vultures optimization algorithm (AVOA). Adopting the AVOA for the best-optimized value (least cost of heat exchanger) and the design parameters are realized, confirming all the constraints. It was found that the AVOA is able to pursue the best results among the rest of them and can be used for the cost optimization of the plate-fin and tube-fin heat exchanger case studies.Publication A multi-strategy boosted prairie dog optimization algorithm for global optimization of heat exchangers(Walter De Gruyter Gmbh, 2023-07-05) Mehtap, Pranav; Sait, Sadiq M.; Kumar, Sumit; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Gürses, Dildar; GÜRSES, DİLDAR; Mühendislik Fakültesi; Makina Mühendisliği Bölümü; JCN-8328-2023; F-7426-2011In this article, a new prairie dog optimization algorithm (PDOA) is analyzed to realize the optimum economic design of three well-known heat exchangers. These heat exchangers found numerous applications in industries and are an imperative part of entire thermal systems. Optimization of these heat exchangers includes knowledge of thermo-hydraulic designs, design parameters and critical constraints. Moreover, the cost factor is always a challenging task to optimize. Accordingly, total cost optimization, including initial and maintenance, has been achieved using multi strategy enhanced PDOA combining PDOA with Gaussian mutation and chaotic local search (MSPDOA). Shell and tube, fin-tube and plate-fin heat exchangers are a special class of heat exchangers that are utilized in many thermal heat recovery applications. Furthermore, numerical evidences are accomplished to confirm the prominence of the MSPDOA in terms of the statistical results. The obtained results were also compared with the algorithms in the literature. The comparison revealed the best performance of the MSPDOA compared to the rest of the algorithm. The article further suggests the adaptability of MSPDOA for various real-world engineering optimization cases.