Optimum Tuning of Mass Dampers by Using a Hybrid Method Using Harmony Search and Flower Pollination Algorithm

In this study, a new approach is proposed for optimization of tuned mass damper positioned on the top of seismic structures. The usage of metaheuristic algorithms is a well-known and effective technique for optimum tuning of parameters such as mass, period and damping ratio. The aim of the study is to generate a new methodology in order to improve the computation capacity and precision of the final results. For that reason, harmony search (HS) and flower pollination algorithm (FPA) are hybridized by proposing a probability based approach. In the methodology, global and local search processes of HS are used together with global and local pollination stages of FPA. In that case, four different types of generation are used. In the methodology, these four types of generation have the same chance at the start of the optimization process and probabilities are reduced when the corresponding type of the generation is chosen. If an improvement is provided for the objective of the optimization, the probability of the effective type is increased. The proposed method has an effective convergence by providing improvement of the optimization objective comparing to classical FPA.

[1]  Anoshirvan Farshidianfar,et al.  OPTIMIZATION OF TMD PARAMETERS FOR EARTHQUAKE VIBRATIONS OF TALL BUILDINGS INCLUDING SOIL STRUCTURE INTERACTION , 2013 .

[2]  Andrew Y. T. Leung,et al.  Particle swarm optimization of tuned mass dampers , 2009 .

[3]  S. Pourzeynali,et al.  Active control of high rise building structures using fuzzy logic and genetic algorithms , 2007 .

[4]  Wei-Ling Chiang,et al.  Wind-induced vibration of high-rise building with tuned mass damper including soil–structure interaction , 2008 .

[5]  Mahendra P. Singh,et al.  Tuned mass dampers for response control of torsional buildings , 2002 .

[6]  Anjan Dutta,et al.  Coupled tuned mass dampers for control of coupled vibrations in asymmetric buildings , 2006 .

[7]  Xin-She Yang,et al.  Review and Applications of Metaheuristic Algorithms in Civil Engineering , 2016 .

[8]  Anooshiravan Farshidianfar,et al.  Ant colony optimization of tuned mass dampers for earthquake oscillations of high-rise structures including soil–structure interaction , 2013 .

[9]  Giuseppe Marano,et al.  A comparison between different optimization criteria for tuned mass dampers design , 2010 .

[10]  Gebrail Bekdaş,et al.  Optimum tuned mass damper design for preventing brittle fracture of RC buildings , 2013 .

[11]  R. S. Jangid,et al.  Optimum parameters of tuned mass damper for damped main system , 2007 .

[12]  Chih-Chen Chang,et al.  Mass dampers and their optimal designs for building vibration control , 1999 .

[13]  Xin-She Yang,et al.  Flower Pollination Algorithm for Global Optimization , 2012, UCNC.

[14]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[15]  Yoyong Arfiadi,et al.  Optimum Design of Absorber for MDOF Structures , 1998 .

[16]  Haijun Zhang,et al.  Particle swarm optimization of TMD by non‐stationary base excitation during earthquake , 2008 .

[17]  Yen-Po Wang,et al.  Optimal design theories and applications of tuned mass dampers , 2006 .

[18]  Gebrail Bekdaş,et al.  ESTIMATING OPTIMUM PARAMETERS OF TUNED MASS DAMPERS USING HARMONY SEARCH , 2011 .

[19]  Anooshiravan Farshidianfar,et al.  ABC optimization of TMD parameters for tall buildings with soil structure interaction , 2013 .

[20]  G. B. Warburton,et al.  Optimum absorber parameters for various combinations of response and excitation parameters , 1982 .

[21]  Rolf Steinbuch,et al.  Bionic optimisation of the earthquake resistance of high buildings by tuned mass dampers , 2011 .

[22]  Fahim Sadek,et al.  A METHOD OF ESTIMATING THE PARAMETERS OF TUNED MASS DAMPERS FOR SEISMIC APPLICATIONS , 1997 .

[23]  T. T. Soong,et al.  Parametric study and simplified design of tuned mass dampers , 1998 .

[24]  Gebrail Bekdaş,et al.  Mass ratio factor for optimum tuned mass damper strategies , 2013 .