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; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv 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 Nature-inspired algorithms for real-life complex engineering problems(Bentham Science Publ Ltd, 2021-01-01) Dhiman, Gaurav; Yıdız, Ali Rıza; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği Bölümü; F-7426-2011Publication Aircraft control parameter estimation using self-adaptive teaching-learning-based optimization with an acceptance probability(Hindawi, 2021-12-01) Kanokmedhakul, Yodsadej; Panagant, Natee; Bureerat, Sujin; Pholdee, Nantiwat; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; 0000-0003-1790-6987; F-7426-2011This work presents a metaheuristic (MH) termed, self-adaptive teaching-learning-based optimization, with an acceptance probability for aircraft parameter estimation. An inverse optimization problem is presented for aircraft longitudinal parameter estimation. The problem is posed to find longitudinal aerodynamic parameters by minimising errors between real flight data and those calculated from the dynamic equations. The HANSA-3 aircraft is used for numerical validation. Several established MHs along with the proposed algorithm are used to solve the proposed optimization problem, while their search performance is investigated compared to a conventional output error method (OEM). The results show that the proposed algorithm is the best performer in terms of search convergence and consistency. This work is said to be the baseline for purely applying MHs for aircraft parameter estimation.Publication Thermodynamic optimization of stirling heat engine with methane gas using finite speed thermodynamic model(Wiley, 2021-08-08) Mansuriya, Kıran; Raja, Bansi D.; Yıldız, Ali Rıza; Mudgal, Anurag; Patel, Vivek K.; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü; 0000-0003-1790-6987; F-7426-2011With the daily rise in environmental issues due to the use of conventional fuels, researchers are motivated to use renewable energy sources. One of such waste heat and low-temperature differential driven energy sources is the Stirling engine. The performance of the Stirling engine can be improved by finding out the optimum operating and geometrical parameters with suitable working gas and thermal model. Based on this motivation, the current work focuses on the multiobjective optimization of the Stirling engine using the finite speed thermodynamic model and methane gas as the working fluid. Considering output power and pressure drop as two objective functions, the system is optimized using 11 geometrical and thermal design parameters. The optimization results are obtained in the form of the Pareto frontier. A sensitivity assessment is carried out to observe the decision variables, which are having a more sensitive effect on the optimization objectives. Optimization results reveal that 99.83% change in power output and 78% change in total pressure drop can take place in the two-dimensional optimization space. The optimal solution closest to the ideal solution has output power and pressure drop values as 12.31 kW and 22.76 kPa, respectively.Publication A comparative study of recent non-traditional methods for mechanical design optimization (vol 27, pg 1031, 2020)(Springer, 2021-01-01) Yıldız, Ali Rıza; Abderazek, Hammoudi; Mirjalili, Seyedali; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Otomotiv Mühendisliği Bölümü; F-7426-2011Publication A novel maximum volume sampling model for reliability analysis(Elsevier Science, 2021-10-10) Meng, Zeng; Pang, Yongsheng; Wu, Zhigen; Ren, Shanhong; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; F-7426-2011In this study, a maximum volume sampling model is proposed to improve the accuracy and efficiency of reliability computation. An ellipsoid is constructed with the maximum volume approach in a safe domain, and a new maximum volume optimization method is proposed. The sampling model only computes the samples outside the ellipsoid, which considerably enhances computational efficiency. Furthermore, the uniform sampling strategy and Givens transformation are adopted to efficiently solve the maximum volume optimization model. A series system example, a three-dimensional rock slope example, and an arch bridge example are tested to verify the validity of the proposed maximum volume sampling model. The results indicate that the maximum volume sampling model displays high accuracy and efficiency.Publication A novel hybrid marine predators-Nelder-Mead optimization algorithm for the optimal design of engineering problems(Walter, 2021-01-01) Panagant, Natee; Yıldız, Mustafa; Pholdee, Nantiwat; Yıldız, Ali Riza; Bureerat, Sujin; Sait, Sadiq M.; YILDIZ, ALİ RIZA; Yıldız, Mustafa; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü; JTZ-2884-2023; F-7426-2011The marine predators optimization algorithm (MPA) is a recently developed nature-inspired algorithm. In this paper, the Nelder-Mead algorithm is utilized to improve the local exploitation powers of the MPA when described as a hybrid marine predators and Nelder-Mead (HMPANM). Due to the harsh competitive conditions as well as the transition to new vehicles such as hybrid and full-electrical cars, the interest in the design of light and low-cost vehicles is increasing. In this study, a recent metaheuristic addition, a hybrid marine predators optimization algorithm, is used to solve a structural design optimization problem to prove how the HMPANM can be used in solving industrial design problems. The results strongly prove the capability of the HMPANM for the optimum design of components in the automotive industry.Publication Optimization of constrained mechanical design problems using the equilibrium optimization algorithm(Walter, 2021-06-01) Abderazek, Hammoudi; Yıldız, Ali Rıza; Sait, Sadiq M.; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomot Mühendisliği Bölümü; 0000-0003-1790-6987; F-7426-2011In this work, the optimization of structural and mechanical problems is carried out using the equilibrium optimizer (EO), which is a recent physical-based algorithm.The the ten-bar planar truss structure, planetary gearbox, hydrostatic thrust bearing, and robot gripper mechanism problems are solved using the EO algorithm. The results achieved using the EO in solving these problems are compared with those of recent algorithms. The computational results show that EO yields better outcomes and competitive results that can also be applied for the other problems studied.Publication Hybrid taguchi-levy flight dis-tribution optimization algorithm for solving real-world design optimization problems(Walter, 2021-06-01) Yıldız, Mustafa; Panagant, Natee; Pholdee, Nantiwat; Bureerat, Sujin; Sait, Sadiq M.; Yıldız, Ali Rıza; Yıldız, Mustafa; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü; F-7426-2011; JTZ-2884-2023The Levy flight distribution optimization algorithm is a recently developed meta-heuristic. In this study, the Levy flight distribution optimization algorithm and the Taguchi method are hybridized to solve the shape optimization problem, which is the final step in developing optimum structural components. The new method is termed the hybrid Levy flight distribution and Taguchi (HLFD-T) algorithm. Geometric dimensions are used as design variables in the optimization, and the problem is aimed at mass minimization. The constraint in the problem is the maximum stress value. The well-known Kriging meta-modeling approach and a specifically developed hybrid approach have been coupled in this paper to find the component's optimal geometry. The results show that the proposed hybrid algorithm (HLFD-T) has more robust features than the ant lion algorithm, the whale algorithm, and the Levy flight distribution optimization algorithm for obtaining an optimal component geometry.Publication Hybrid spotted hyena-Nelder-Mead optimization algorithm for selection of optimal machining parameters in grinding operations(Walter De Gruyter Gmbh, 2021-01-01) Pholdee, Nantiwat; Patel, Vivek K.; Sait, Sadiq M.; Bureerat, Sujin; Yıldız, Ali Rıza; YILDIZ, ALİ RIZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; F-7426-2011In this research, a novel optimization algorithm, which is a hybrid spotted hyena-Nelder-Mead optimization algorithm (HSHO-NM) algorithm, has been introduced in solving grinding optimization problems. A well-known grinding optimization problem is solved to prove the superiority of the HSHO-NM over other algorithms. The results of the HSHO-NM are compared with others. The results show that HSHO-NM is an efficient optimization approach for obtaining the optimal manufacturing variables in grinding operations.