An ant colony algorithm applied to lay-up optimization of laminated composite plates

ant colony optimization (aco) is a class of heuristic algorithms proposed to solve optimization problems. the idea was inspired by the behavior of real ants, related to their ability to find the shortest path between the nest and the food source. aco has been applied successfully to different kinds of problems. so, this manuscript describes the development and application of an aco algorithm to find the optimal stacking sequence of laminated composite plates. the developed aco algorithm was evaluated on four examples for symmetric and balanced lay-up. the results of the first three cases, in which the classical lamination theory was used to obtain the structural response of rectangular plates, were compared to those obtained from the literature using genetic algorithms (ga) and other aco algorithm. the fourth example investigates the maximization of fundamental frequencies of rectangular plates with central holes, where the structural response was obtained by finite element analysis, showing that this optimization technique may be successfully applied to a broad class of stacking sequence problems for laminated composites.