Browsing by Author "Abderazek, Hammoudi"
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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-7426-2011Item Comparative investigation of the moth-flame algorithm and whale optimization algorithm for optimal spur gear design(Walter De Gruyter GMBH, 2021-03) Abderazek, Hammoudi; Hamza, Ferhat; Sait, Sadiq M.; Yıldız, Ali Rıza; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği.; 0000-0003-1790-6987; F-7426-2011; 7102365439In this study, two recent algorithms, the whale optimization algorithm and moth-flame optimization, are used to optimize spur gear design. The objective function is the minimization of the total weight of the spur gear pair. Moreover, the optimization problem is subjected to constraints on the main kinematic and geometric conditions as well as to the resistance of the material of the gear system. The comparison between mothflame optimization (MFO), the whale optimization algorithm (WOA), and previous studies indicate that the final results obtained from both algorithms lead to a reduction in gear weight by 1.05 %. MFO and the WOA are compared with four additional swarm algorithms. The experimental results indicate that the algorithms introduced here, in particular MFO, outperform the four other methods when compared in terms of solution quality, robustness, and high success rate.Item Comparison of metaheuristic optimization algorithms for solving constrained mechanical design optimization problems(Pergamon-Elsevier Science Ltd, 2021-11-30) Gupta, Shubham; Abderazek, Hammoudi; Mirjalili, Seyedali; Sait, Sadiq M.; Yıldız, Betül Sultan; Yıldız, Ali Rıza; Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği.; AAL-9234-2020; F-7426-2011; 57094682600; 7102365439Determining the solution for real mechanical design problems is a challenging task when using the newly developed and efficient swarm intelligence algorithms. There are so many difficulties to be addressed, including but not limited to mixed decision variables, diverse constraints, inherent errors, conflicting objectives, and numerous locally optimal solutions. This work analyzes the behavior of nine metaheuristic algorithms, namely, salp swarm algorithm (SSA), multi-verse optimizer (MVO), moth-flame optimizer (MFO), atom search optimi-zation (ASO), ecogeography-based optimization (EBO), queuing search algorithm (QSA), equilibrium optimizer (EO), evolutionary strategy (ES) and hybrid self-adaptive orthogonal genetic algorithm (HSOGA). The efficiency of these algorithms is evaluated on eight mechanical design problems using the solution quality and convergence analysis, which verifies the wide applicability of these algorithms to real-world application problems.Item Comparison of recent optimization algorithms for design optimization of a cam-follower mechanism(Elsevier, 2019-11-12) Abderazek, Hammoudi; Mirjalili, Seyedali; Yıldız, Ali Rıza; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; 0000-0003-1790-6987; 7102365439This study presents the application of seven recent meta-heuristic optimization algorithms to automate design of disk cam mechanism with translating roller follower regarding four follower motion laws. The algorithms are: salp swarm algorithm (SSA), moth-flame optimization (MFO), ant lion optimizer (ALO), multi verse optimizer (MVO), grey wolf optimizer (GWO), evaporation rate water cycle algorithm (ER-WCA), and mine blast algorithm (MBA). The optimum cam design problem is formulated with three objectives including the minimum congestion, maximum performance, and maximum strength resistance of the cam. Moreover, the effect of selecting follower motion law on the optimal design of mechanism is investigated. The computational results clearly indicate that the utilized algorithms are very competitive in structural design optimization, especially MBA, ER-WCA, MFO and GWO techniques. Among the four follower motion laws, the polynomial 3-4-5 degree is the best one.Item Mechanical engineering design optimisation using novel adaptive differential evolution algorithm(Inderscience Enterprises, 2019) Abderazek, Hammoudi; Sait, Sadiq M.; Yıldız, Ali Rıza; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; F-7426-2011; 7102365439This paper introduces a new adaptive mixed differential evolution (NAMDE) algorithm for mechanical design optimisation problems. The algorithm uses a self-adaptive mechanism to update the values of mutation and crossover factors. Moreover, elitism is used where the best-found individual in each generation is retained. The performance of NAMDE is evaluated by solving 11 well-known constrained mechanical design problems and two industrial applications. Further, comparison results between NAMDE and other recently published methods, for the first problems, clearly illustrate that the proposed approach is an important alternative to solve current real-world optimisation problems. Besides this, new optimal solutions for some engineering problems are obtained and reported in this paper. For the coupling with a bolted rim problem, the objective function improved by 10%. Whereas for the spur minimisation problem, the final design provides a reduction in gearing mass by 7.5% compared to those published in previous works.Item Optimal design of planetary gear train for automotive transmissions using advanced meta-heuristics(Inderscience Enterprises, 2019) Abderazek, Hammoudi; Sait, Sadiq M.; Yıldız, Ali Rıza; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; F-7426-2011In this paper, nine recent meta-heuristics have been employed to search for optimal design of an automatic planetary gear train. The function of the designed system is to automatically transmit power and motion in automobiles. Nine mixed decision parameters are considered in the optimisation procedure. The geometric conditions such as the undercutting, the maximum overall diameter of the transmission, as well as the spacing of multiple planets are taken into account to ensure an optimum design. All the above algorithms are tested both quantitatively and qualitatively for solution quality, robustness, and their time complexity is determined. Results obtained illustrate that the utilised approaches can effectively solve the planetary gearbox problem. Besides this, the comparative study indicates that roulette wheel selection-elitist differential evolution (ReDE) outperforms the other algorithms in terms of the statistical results, and FA has the best convergence behaviour. Meanwhile, multi-verse optimisation (MVO) and butterfly optimisation algorithm (BOA) performed better than the other used algorithms when computation time was considered.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.Item Optimum design of cam-roller follower mechanism using a new evolutionary algorithm(Springer, 2018-08-09) Hamza, Ferhat; Abderazek, Hammoudi; Lakhdar, Smata; Ferhat, Djeddou; Yıldız, Ali Rıza; Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.; 0000-0003-1790-6987; F-7426-2011; 7102365439The optimum design of a cam mechanism is a very interesting problem in the contact mechanics today, due to the alternative industrial applications as a mechanism of precision. In this paper, a new evolutionary algorithm called modified adaptive differential evolution (MADE) is introduced for multi-objective optimization of a cam mechanism with offset translating roller follower. The optimization procedure is investigated for three objectives among them minimum congestion, maximum efficiency, and maximum strength resistance of the cam. To enhance the design quality of the mechanism in the optimization process, more geometric parameters and more design constraints are included in the problem formulation. In order to validate the developed algorithm, three engineering design problems are solved. The simulation results for the tested problems indicate the effectiveness and the robustness of the proposed algorithm compared to the various existed optimization methods. Finally, the optimal results obtained for the case study example provide very useful decisions for a cam mechanism synthesis.