Browsing by Author "Kaen, Khon"
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Item Comparision of the political optimization algorithm, the Archimedes optimization algorithm and the Levy flight algorithm for design optimization in industry(Walter De Gruyter GMBH, 2021-04) Pholdee, Nantiwat; Bureerat, Sujin; Kaen, Khon; Sait, Sadiq M.; Yıldız, Betül Sultan; Erdaş, Mehmet Umut; Yıldız, Ali Rıza; Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği.; Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği.; AAL-9234-2020; F-7426-2011; CNV-1200-2022; 57094682600; 57298176600; 7102365439This article focuses on minimizing product costs by using the newly developed political optimization algorithm (POA), the Archimedes 'optimization algorithm (AOA), and the Levy flight algorithm (LFA) in product development processes. Three structural optimization methods, size optimization, shape optimization, and topology optimization, are extensively applied to create inexpensive structures and render designs efficient. Using size, shape, and topology optimization in an integrated way, It is possible to obtain the most efficient structures in industry. The political optimization algorithm (POA) is a metaheuristic algorithm that can be used to solve many optimization problems. This study investigates the search capability and computational efficiency of POA for optimizing vehicle structures. By examining the results obtained, we prove the apparent superiority of the POA to other recent famous metaheuristics such as the Archimedes optimization algorithm and the Levy flight algorithm. The most important result of this paperwill be to provide an impressive aid for industrial companies to fill the gaps in their product design stages.Item A novel hybrid Harris hawks-simulated annealing algorithm and RBF-based metamodel for design optimization of highway guardrails(Walter de Gruyter, 2020-02-25) Kaen, Khon; Sait, Sadiq; Yıldız, Ali Rıza; Kurtuluş, Enes; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği.; 0000-0003-1790-6987; 7102365439; 56534007500In this paper, a novel hybrid optimization algorithm is introduced by hybridizing a Harris hawks optimization algorithm(HHO) and simulated annealing for the purpose of accelerating its global convergence performance and optimizing structural design problems. This paper is the first research study in which the hybrid Harris hawks simulated annealing algorithm (HHOSA) is used for the optimization of design parameters for highway guardrail systems. The HHOSA is evaluated using the well-known benchmark problems such as the three-bar truss problem, cantilever beam problem, and welded beam problem. Finally, a guardrail system that has an H1 containment level as a case study is optimized to investigate the performance of the HHOSA. The guardrail systems are designed with different cross-sections and distances between the posts. TB11 and TB42 crash analyses are performed according to EN 1317 standards. Twenty-five different designs are evaluated considering weight, the guardrail working width, and the acceleration severity index (ASI). As a result of this research, the optimum design of a guardrail is obtained, which has a minimum weight and acceleration severity index value (ASI). The results show that the HHOSA is a highly effective approach for optimizing real-world design problems.