fd5094b8-77e8-4da3-b12f-0fd131fa550b20210316035030196wseamdt@crossref.orgMDT DepositWSEAS TRANSACTIONS ON COMPUTERS1109-275010.37394/23205http://wseas.org/wseas/cms.action?id=40262720202720201910.37394/23205.2020.19http://wseas.org/wseas/cms.action?id=23186Minimizing the Weight of Cantilever Beam via Metaheuristic Methods by Using Different Population-Iteration CombinationsMeldaYücelDepartment of Civil Engineering, Istanbul University-Cerrahpaşa, Istanbul, TurkeyGebrai̇lBekdaşDepartment of Civil Engineering, Istanbul University-Cerrahpaşa, Istanbul, TurkeySi̇nan Meli̇hNi̇gdeli̇Department of Civil Engineering, Istanbul University-Cerrahpaşa, Istanbul, TurkeySince a long time, metaheuristic algorithms are benefited to detect the best results for any optimization problem. Furthermore, these methods are used to prevent of time, effort and cost losses, while they are performing the optimization process. Hence, in this study, a cantilever beam model, which is one of the structural optimization problem from civil engineering area, was handled with the aim of minimization of the total weight by find the optimum section values consisting of hollow section depths and widths. For this reason, three different methods including the algorithms that artificial bee colony (ABC), bat (BA), and a modified bat (MBA) combining of BA with Lévy flight, were operated. Additionally, several applications previously carried out for this model, were presented in order to compare of optimization results (minimum objective function with optimum design variable values), and success of proposed algorithm was showed with statistical results and optimization parameter values.4820204820206977https://www.wseas.org/multimedia/journals/computers/2020/a205105-059.pdf10.37394/23205.2020.19.10http://www.wseas.org/multimedia/journals/computers/2020/a205105-059.pdf10.1016/j.trpro.2015.09.045Marinelli, M., Palmisano, G., Dell’orco, M., Ottomanelli, M., 2015, Fusion of two metaheuristic approaches to solve the flight gate assignment problem, Transportation Research Procedia, 10, 920-930. 10.1016/j.procs.2016.07.333Shilaja, C., Ravi, K., 2016, Optimal power flow, sizing and location of thermal generating units using metaheuristic soft computing algorithms, Procedia Computer Science, 92, 119-127.10.1016/j.trd.2018.06.003Gujarathi, P.K., Shah, V.A., Lokhande, M.M., 2018, Grey wolf algorithm for multidimensional engine optimization of converted plug-in hybrid electric vehicle, Transportation Research Part D: Transport and Environment, 63, 632-648.10.1016/j.knosys.2017.01.026Ehteram, M., Karami, H., Mousavi, S. 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