Person: YILDIZ, ALİ RIZA
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YILDIZ
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ALİ RIZA
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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 Optimal design of aerospace structures using recent meta-heuristic algorithms(Walter de Gruyter Gmbh, 2021-11-01) Korkmaz, Faik Fatih; Yıldız, Ali Riza; Subran, Mert; Korkmaz, Faik Fatih; YILDIZ, ALİ RIZA; Türk Havacılık ve Uzay Sanayi Ar Ge Merkezi; 0000-0003-1790-6987; KUC-9229-2024; F-7426-2011Most conventional optimization approaches are deterministic and based on the derivative information of a problem's function. On the other hand, nature-inspired and evolution-based algorithms have a stochastic method for finding the optimal solution. They have become a more popular design and optimization tool, with a continually growing development of novel algorithms and new applications. Flexibility, easy implementation, and the capability to avoid local optima are significant advantages of these algorithms. In this study, shapes, and shape perturbation limits of a bracket part, which is used in aviation, have been set using the hypermorph tool. The objective function of the optimization problem is minimizing the volume, and the constraint is maximum von Mises stress on the structure. The grey wolf optimizer (GWO) and the moth-flame Optimizer (MFO) have been selected as nature-inspired evolution-based optimizers.Publication Experimental investigation of mechanical properties of PLA, ABS, and PETG 3-d printing materials using fused deposition modeling technique(Walter De Gruyter Gmbh, 2023-09-08) Kopar, Mehmet; Yıldız, Ali Rıza; Kopar, Mehmet; YILDIZ, ALİ RIZA; Mühendislik Fakültesi; Otomotiv Mühendisliği Bölümü; 0000-0003-1790-6987; F-7426-2011; DBQ-9849-2022In recent years, there has been a logarithmic interest in three-dimensional printing technologies. This technique has made it possible to make more intricately shaped parts of superior quality, allowing for use in a variety of industries, including aircraft, automobiles, and ships. This study characterized the materials and assessed the mechanical features of PLA, PETG, and ABS materials generated at various raster angles. The strength ratios of the various materials have been found to fluctuate when the raster angles change. The PLA parts created at a picture raster angle of 45 degrees had the maximum tensile strength. ABS material created with a picture raster angle of 45 degrees has been shown to have the best energy absorption, and PLA material made with a raster angle of 45 degrees has the best performance compressive strength. When bending strength was evaluated, it was found that samples of ABS made with a raster angle of 0-90 degrees had the greatest value. The SEM micrographs were obtained, and the tensile test was used to examine the fracture behavior of the materials. As a result, it has been found that materials created using various raster angles can have various strength values from one another.Publication Simultaneous aerodynamic and structural optimisation of a low-speed horizontal-axis wind turbine blade using metaheuristic algorithms(Walter de Gruyter Gmbh, 2023-04-12) Sabangban, Numchoak; Panagant, Natee; Bureerat, Sujin; Wansasueb, Kittinan; Kuma, Sumit; Yıldız, Ali Riza; Pholdee, Nantiwat; YILDIZ, ALİ RIZA; Makine Mühendisliği Bölümü; F-7426-2011This work presents a concurrent design and multi-objective optimisation framework of horizontal axis wind turbine blades, made of composite material, for low wind speed. The optimisation model aims to minimise the structural mass of the blade whilst simultaneously maximising the turbine power output, subjected to three constraints viz. blade tip deflection, and Tsai-Hill and von Mises criteria. The design variables are blade shape and details of the internal blade structure. The control points and polynomial interpolation technique were adopted to determine the blade shape while the airfoil types at blade sections remained fixed. The internal blade structure design variables include the thickness of ribs and spars and the carbon fibre thickness and orientations. The blade element momentum approach is utilised to calculate turbine power and structural loads, whereas a finite element method is employed for structural analysis. Twelve multi-objective metaheuristics algorithms are used to solve the proposed multi-objective optimisation problem while their performance is investigated. The results obtained show that the multi-objective cuckoo search algorithm is the most efficient method. This study is said to be the baseline for a future study on multi-objective optimisation which combines two design stages of the composite low-speed wind turbine blades.Publication A comparative study of state-of-the-art metaheuristics for solving many-objective optimization problems of fixed wing unmanned aerial vehicle conceptual design(Springer, 2023-04-11) Anosri, Siwakorn; Panagant, Natee; Champasak, Pakin; Bureerat, Sujin; Thipyopas, Chinnapat; Kumar, Sumit; Pholdee, Nantiwat; Yıldız, Betül Sultan; Yıldız, Ali Riza; YILDIZ, ALİ RIZA; YILDIZ, BETÜL SULTAN; Mühendislik Fakültesi; Makine Mühendisliği Bölümü; 0000-0001-7592-8733 ; AAH-6495-2019; F-7426-2011The complexity of aircraft design problems increases with many objectives and diverse constraints, thus necessitating effective optimization techniques. In recent years many new metaheuristics have been developed, but their implementation in the design of the aircraft is limited. In this study, the effectiveness of twelve new algorithms for solving unmanned aerial vehicle design issues is compared. The optimizers included Differential evolution for multi-objective optimization, Many-objective nondominated sorting genetic algorithm, Knee point-driven evolutionary algorithm for many-objective optimization, Reference vector guided evolutionary algorithm, Multi-objective bat algorithm with nondominated sorting, multi-objective flower pollination algorithm, Multi-objective cuckoo search algorithm, Multi-objective multi-verse optimizer, Multi-objective slime mould algorithm, Multi-objective jellyfish search algorithm, Multi-objective evolutionary algorithm based on decomposition and Self-adaptive many-objective meta-heuristic based on decomposition. The design problems include four many-objective conceptual designs of UAV viz. Conventional, Conventional with winglet, Twin boom and Canard, which are solved by all the optimizers employed. Widely used Hypervolume and Inverted Generational Distance metrics are considered to evaluate and compare the performance of examined algorithms. Friedman's rank test based statistical examination manifests the dominance of the DEMO optimization technique over other compared techniques and exhibits its effectiveness in solving aircraft conceptual design problems. The findings of this work assist in not only solving aircraft design problems but also facilitating the development of unique algorithms for such challenging issues.Publication A novel hybrid fick's law algorithm-quasi oppositional-based learning algorithm for solving constrained mechanical design problems(Walter De Gruyter Gmbh, 2023-09-13) Mehta, Pranav; Sait, Sadiq M.; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Yıldız, Betül Sultan; YILDIZ, BETÜL SULTAN; Mühendislik Fakültesi; Makina Mühendisliği Bölümü; AAL-9234-2020; F-7426-2011In this article, a recently developed physics-based Fick's law optimization algorithm is utilized to solve engineering optimization challenges. The performance of the algorithm is further improved by incorporating quasi-oppositional-based techniques at the programming level. The modified algorithm was applied to optimize the rolling element bearing system, robot gripper, planetary gear system, and hydrostatic thrust bearing, along with shape optimization of the vehicle bracket system. Accordingly, the algorithm realizes promising statistical results compared to the rest of the well-known algorithms. Furthermore, the required number of iterations was comparatively less required to attain the global optimum solution. Moreover, deviations in the results were the least even when other optimizers provided better or more competitive results. This being said that this optimization algorithm can be adopted for a critical and wide range of industrial and real-world challenges optimization.Publication Hunger games search algorithm for global optimization of engineering design problems(Walter De Gruyter Gmbh, 2022-04-26) Mehta, Pranav; Yıldız, Betül Sultan; Sait, Sadiq M.; Yıldız, Ali Rıza; YILDIZ, BETÜL SULTAN; YILDIZ, ALİ RIZA; Mühendislik Fakültesi; Elektrik ve Enerji Bölümü; F-7426-2011; AAL-9234-2020The modernization in automobile industries has been booming in recent times, which has led to the development of lightweight and fuel-efficient design of different automobile components. Furthermore, metaheuristic algorithms play a significant role in obtaining superior optimized designs for different vehicle components. Hence, a hunger game search (HGS) algorithm is applied to optimize the automobile suspension arm (SA) by reduction of mass vis-a-vis volume. The performance of the HGS algorithm was accomplished by comparing the achieved results with the well-established metaheuristics (MHs), such as salp swarm optimizer, equilibrium optimizer, Harris Hawks optimizer (HHO), chaotic HHO, slime mould optimizer, marine predator optimizer, artificial bee colony optimizer, ant lion optimizer, and it was found that the HGS algorithm is able to pursue the best optimized solution subjecting to critical constraints. Moreover, the HGS algorithm can realize the least weight of the SA subjected to maximum stress values. Hence, the adopted algorithm can be found robust in terms of obtaining the best global optimum solution.Publication A new hybrid artificial hummingbird-simulated annealing algorithm to solve constrained mechanical engineering problems(Walter de Gruyter Gmbh, 2022-07-26) Yıldız, Betül Sultan; Mehta, Pranav; Sait, Sadiq M.; Panagant, Natee; Kumar, Sumit; Yıldız, Ali Rıza; YILDIZ, BETÜL SULTAN; YILDIZ, ALİ RIZA; Mühendislik Fakültesi; Makine Mühendisliği Bölümü; AAL-9234-2020; F-7426-2011Nature-inspired algorithms known as metaheuristics have been significantly adopted by large-scale organizations and the engineering research domain due their several advantages over the classical optimization techniques. In the present article, a novel hybrid metaheuristic algorithm (HAHA-SA) based on the artificial hummingbird algorithm (AHA) and simulated annealing problem is proposed to improve the performance of the AHA. To check the performance of the HAHA-SA, it was applied to solve three constrained engineering design problems. For comparative analysis, the results of all considered cases are compared to the well-known optimizers. The statistical results demonstrate the dominance of the HAHA-SA in solving complex multi-constrained design optimization problems efficiently. Overall study shows the robustness of the adopted algorithm and develops future opportunities to optimize critical engineering problems using the HAHA-SA.Publication A novel generalized normal distribution optimizer with elite oppositional based learning for optimization of mechanical engineering problems(Gmbh, 2023-02-23) Mehta, Pranav; Yıldız, Betuel Sultan; Pholdee, Nantiwat; Kumar, Sumit; Riza Yıldız, Ali; Sait, Sadiq M. M.; Bureerat, Sujin; YILDIZ, BETÜL SULTAN; YILDIZ, ALİ RIZA; Mühendislik Fakültesi; Makine Mühendisliği Bölümü; F-7426-2011; AAH-6495-2019Optimization of engineering discipline problems are quite a challenging task as they carry design parameters and various constraints. Metaheuristic algorithms can able to handle those complex problems and realize the global optimum solution for engineering problems. In this article, a novel generalized normal distribution algorithm that is integrated with elite oppositional-based learning (HGNDO-EOBL) is studied and employed to optimize the design of the eight benchmark engineering functions. Moreover, the statistical results obtained from the HGNDO-EOBL are collated with the data obtained from the well-established algorithms such as whale optimizer, salp swarm optimizer, LFD optimizer, manta ray foraging optimization algorithm, hunger games search algorithm, reptile search algorithm, and INFO algorithm. For each of the cases, a comparison of the statistical results suggests that HGNDO-EOBL is superior in terms of realizing the prominent values of the fitness function compared to established algorithms. Accordingly, the HGNDO-EOBL can be adopted for a wide range of engineering optimization problems.Publication Nature-inspired algorithms for real-life complex engineering problems(Bentham Science Publ Ltd, 2021-01-01) Dhiman, Gaurav; Yıdız, Ali Rıza; YILDIZ, ALİ RIZA; Mühendislik Fakültesi; Makina Mühendisliği Bölümü; F-7426-2011