2017 Cilt 22 Sayı 3

Permanent URI for this collectionhttps://hdl.handle.net/11452/12075

Browse

Browsing by Subject "Ant colony optimization"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Determination the number of ants used in aco algorithm via grillage optimization
    (Uludağ Üniversitesi, 2017-12-27) Aydın, Zekeriya
    Ant colony optimization (ACO) algorithm is one of the artificial intelligence methods used in structural optimization. Values of some optimization parameters must be determined before the optimization process in most of the artificial intelligence based optimization algorithms. Determination of the values of these optimization parameters is essential especially for the time required for the optimization process and the quality of results achieved. Pheromone update coefficient, number of ants in the colony, number of depositing ants, penalty coefficient are the main optimization parameters in ACO algorithm. This study is focused on the number of ants in the ant colony. This research is realized using the optimization of grillage structure which is one of the well-known optimization problems in the literature. Minimization of the weight of structure is the objective function of the optimization problem, and the member sizes of grillages are considered as discrete design variables. Displacement and strength restrictions are considered as constraints according to manual of LRFD-AISC. A computer program is coded in BASIC to accomplish the structural design and optimization procedures. Numerical examples from literature are optimized using different number of ants to determine the effect of the number of ants on the optimization process. At the end of the study, some inferences are presented on the number of ants to be used in the colony.