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A novel hybrid marine predators-Nelder-Mead optimization algorithm for the optimal design of engineering problems

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Akademik Birimler

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Yıldız, Mustafa

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Panagant, Natee
Yıldız, Mustafa
Pholdee, Nantiwat
Yıldız, Ali Riza
Bureerat, Sujin
Sait, Sadiq M.

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Walter

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The 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.

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Differential evolution, Structural design, Water cycle, Search, Crashworthiness, Performance, Whale, Marine predators optimization algorithm, Nelder-mead, Shape optimization, Vehicle design, Optimum design, Science & technology, Technology, Materials science, characterization & testing

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