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Showing 3 results for Artificial Bee Colony (abc)

A. Farshidianfar, S. Soheili,
Volume 3, Issue 3 (9-2013)
Abstract

This paper investigates the optimized parameters of Tuned Mass Dampers (TMDs) for high-rise structures considering Soil Structure Interaction (SSI) effects. Three optimization methods, namely the ant colony optimization (ACO) technique together with artificial bee colony (ABC) and shuffled complex evolution (SCE) methods are utilized for the optimization of TMD Mass, damping coefficient and spring stiffness as the design variables. The objective is to decrease the maximum displacement of structure. The 40 story structure with three soil types is employed to design TMD for six types of far field earthquakes. The results are then utilized to obtain relations for the optimized TMD parameters with SSI effects. The relations are then applied to design TMD for the same structure with another five types of far field oscillations, and reasonable results are achieved. For further investigations, the obtained relations are utilized to design TMD for a new structure, and the reduction values are obtained for five types of earthquakes, which show acceptable results. This study improves the understanding of earthquake oscillations, and helps the designers to achieve the optimized TMD for high-rise buildings.
S.a.r. Mirbod, M. Daei, H. Tajmir Riahi,
Volume 7, Issue 1 (1-2017)
Abstract

In this paper, the effective parameters on the ductility demand of the seismically base isolated structure are investigated, and then a relation between the strength reduction factor and the target ductility is presented. The investigation has been conducted by modelling the base isolated structure as a two degree of freedom model in the OpenSees software, and the possibility of yielding in the superstructure has been considered in the model. Results show that the period of isolator and superstructure have the most effect on the ductility demand, therefore these two parameters beside the strength reduction factor and the target ductility have been used as variables of  relation. A nonlinear regression model has been developed for forecasting the relation and the constant parameters of the proposed scheme has been obtained based on an optimization model solved by modified artificial bee colony (ABC) algorithm. A database including 224 models under 20 earthquake records with 2% probability of exceedance in 50 years have been generated for this purpose. Since there is not any explicit closed form formula to calculate the strength reduction factor for a specific target ductility; another optimization model has been developed to calculate the data used as input of the nonlinear regression model. The proposed relation includes two nonlinear functions and it is able to quantify the inelastic performance of base isolated structures for a wide range of earthquake records accurately.


A. Kaveh, A. Dadras,
Volume 8, Issue 2 (8-2018)
Abstract

In this paper the performance of four well-known metaheuristics consisting of Artificial Bee Colony (ABC), Biogeographic Based Optimization (BBO), Harmony Search (HS) and Teaching Learning Based Optimization (TLBO) are investigated on optimal domain decomposition for parallel computing. A clique graph is used for transforming the connectivity of a finite element model (FEM) into that of the corresponding graph, and k-median approach is employed. The performance of these methods is investigated through four FE models with different topology and number of meshes. A comparison of the numerical results using different algorithms indicates, in most cases the BBO is capable of performing better or identical using less time with equal computational effort.

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