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.
Optimization of laminate stacking sequence for maximum buckling load using the ant colony optimization (ACO)metaheuristic
AYMERICH, FRANCESCO;SERRA, MAURO
2008-01-01
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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