A hybrid optimization algorithm for gate locations in the liquid composite molding process
It is costly to optimize the location of multiple injection gates through a trial and error-based method in the liquid composite molding, even though there are high fidelity physics-based numerical models. A hybrid optimization method called the Simulated Annealing Genetic Algorithm is proposed in t...
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| Published in | Textile research journal Vol. 92; no. 23-24; pp. 4912 - 4920 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
London, England
SAGE Publications
01.12.2022
Sage Publications Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0040-5175 1746-7748 1746-7748 |
| DOI | 10.1177/00405175221109625 |
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| Abstract | It is costly to optimize the location of multiple injection gates through a trial and error-based method in the liquid composite molding, even though there are high fidelity physics-based numerical models. A hybrid optimization method called the Simulated Annealing Genetic Algorithm is proposed in this article, which uses the genetic algorithm to provide a global search for a predetermined time and then is further improved by the simulated annealing algorithm. The optimization results of multiple injection gates show that the number of convergence iterations using the Simulated Annealing Genetic Algorithm is less than that using the genetic algorithm, and the phenomenon becomes more obvious as the number of injection gates increases. The case shows that the Simulated Annealing Genetic Algorithm can solve the multiple injection gate configuration problems of highly anisotropic laminates without extra work. The optimization results are in good agreement with the experimental results. |
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| AbstractList | It is costly to optimize the location of multiple injection gates through a trial and error-based method in the liquid composite molding, even though there are high fidelity physics-based numerical models. A hybrid optimization method called the Simulated Annealing Genetic Algorithm is proposed in this article, which uses the genetic algorithm to provide a global search for a predetermined time and then is further improved by the simulated annealing algorithm. The optimization results of multiple injection gates show that the number of convergence iterations using the Simulated Annealing Genetic Algorithm is less than that using the genetic algorithm, and the phenomenon becomes more obvious as the number of injection gates increases. The case shows that the Simulated Annealing Genetic Algorithm can solve the multiple injection gate configuration problems of highly anisotropic laminates without extra work. The optimization results are in good agreement with the experimental results. |
| Author | Liu, Junling Chen, Li Xie, Junbo |
| Author_xml | – sequence: 1 givenname: Junling orcidid: 0000-0001-7583-2088 surname: Liu fullname: Liu, Junling organization: Ministry of Education Key Laboratory of Advanced Textile Composite Materials, TianGong University, PR China – sequence: 2 givenname: Junbo surname: Xie fullname: Xie, Junbo organization: Ministry of Education Key Laboratory of Advanced Textile Composite Materials, TianGong University, PR China – sequence: 3 givenname: Li surname: Chen fullname: Chen, Li email: chenli@tiangong.edu.cn organization: Ministry of Education Key Laboratory of Advanced Textile Composite Materials, TianGong University, PR China |
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| Cites_doi | 10.1016/j.nanoen.2022.107114 10.1016/j.compositesa.2011.04.021 10.1002/(SICI)1097-0363(19961015)23:7<661::AID-FLD448>3.0.CO;2-E 10.1016/S1359-835X(99)00054-8 10.1177/002199839402801202 10.1177/00405175211050517 10.1080/00207540600806455 10.1002/pc.10571 10.1016/S1359-835X(01)00146-4 10.1016/j.compositesa.2021.106540 10.1002/pc.10050 10.1016/j.compositesa.2007.04.008 10.1002/pc.10344 10.1088/0965-0393/12/3/S08 10.1016/j.compositesa.2019.105499 10.1016/S0278-6125(04)80039-6 10.1016/j.compositesa.2017.01.003 10.1016/j.compositesa.2016.04.026 10.1016/j.asoc.2008.05.008 10.1016/j.compositesa.2007.03.005 10.1016/S1359-835X(00)00147-0 10.1080/20550340.2019.1565648 10.1016/S1359-835X(02)00047-7 10.1016/0898-1221(92)90094-X 10.1016/j.compositesa.2016.09.023 |
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| SubjectTerms | Algorithms anisotropy fabrics Gates Genetic algorithms Injection Laminates Liquid composite molding liquids Mathematical models Numerical models Optimization Simulated annealing Simulation system optimization |
| Title | A hybrid optimization algorithm for gate locations in the liquid composite molding process |
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