Hybrid inner-outer algorithm for solving real-world mechanical optimization problems
Abstract In the real world, the problems mostly are complex; more precisely, the problems generally are nonlinear or large scale other than if it was mandatory to resolve it under certain constraints, and that is common in engineering design problems. Therefore, the complexity of problem plays a cri...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
SpringerOpen
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/cac05aee9b0048c481e7de6a23aa34e6 |
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| Sumario: | Abstract In the real world, the problems mostly are complex; more precisely, the problems generally are nonlinear or large scale other than if it was mandatory to resolve it under certain constraints, and that is common in engineering design problems. Therefore, the complexity of problem plays a critical role in determining the computational time and cost. Accordingly, a novel algorithm called inner-outer array is proposed in this paper. It depends on the design of parameters and then tolerance design as one of design of experiment stages. In this work, the inner-outer algorithm is used to solve real-world optimization problems to choose the preferable feasible regions of the entire search domain. Numerical results are documented and compared based on four well-known constrained mechanical engineering issues. It can be concluded that the performance of inner-outer algorithm is good to optimize constrained engineering problems, but it still needs some enhancements in the future work. |
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