Optimization of laminate stacking sequence for maximum buckling load using the ant colony optimization (ACO) metaheuristic
The paper illustrates the application of the ant colony optimization (ACO) metaheuristic to the lay-up design of laminated panels for maximization of buckling load with strength constraints. A specific problem previously studied by different researchers using genetic algorithms (GA) and Tabu search...
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| Published in | Composites. Part A, Applied science and manufacturing Vol. 39; no. 2; pp. 262 - 272 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Elsevier Ltd
01.02.2008
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1359-835X 1878-5840 |
| DOI | 10.1016/j.compositesa.2007.10.011 |
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| Abstract | The paper illustrates the application of the ant colony optimization (ACO) metaheuristic to the lay-up design of laminated panels for maximization of buckling load with strength constraints. A specific problem previously studied by different researchers using genetic algorithms (GA) and Tabu search (TS) was chosen as a test-case to characterize the computational efficiency and the quality of results provided by the developed ACO algorithm. The results of numerical experiments, based on the use of a single ant per search run, show that the average performance and the robustness of the ACO search strategy is comparable or better than that of optimization procedures based on GA or TS. |
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| AbstractList | The paper illustrates the application of the ant colony optimization (ACO) metaheuristic to the lay-up design of laminated panels for maximization of buckling load with strength constraints. A specific problem previously studied by different researchers using genetic algorithms (GA) and Tabu search (TS) was chosen as a test-case to characterize the computational efficiency and the quality of results provided by the developed ACO algorithm. The results of numerical experiments, based on the use of a single ant per search run, show that the average performance and the robustness of the ACO search strategy is comparable or better than that of optimization procedures based on GA or TS. |
| Author | Serra, M. Aymerich, F. |
| Author_xml | – sequence: 1 givenname: F. surname: Aymerich fullname: Aymerich, F. email: aymerich@iris.unica.it organization: Dipartimento di Ingegneria Meccanica, Università di Cagliari, Cagliari, Italy – sequence: 2 givenname: M. surname: Serra fullname: Serra, M. organization: Dipartimento di Ingegneria Strutturale, Università di Cagliari, Cagliari, Italy |
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| Keywords | Ant colony optimization (ACO) B. Buckling A. Laminates Stacking sequence Laminate Genetic algorithm Fiber reinforced material Optimization method Theoretical study Numerical simulation Buckling Composite material |
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| SubjectTerms | A. Laminates Ant colony optimization (ACO) B. Buckling Buckling Exact sciences and technology Fundamental areas of phenomenology (including applications) Physics Solid mechanics Structural and continuum mechanics |
| Title | Optimization of laminate stacking sequence for maximum buckling load using the ant colony optimization (ACO) metaheuristic |
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