Estimating optimum parameters of tuned mass dampers using harmony search

Bekdaş, Gebrai̇l; Niğdeli, Sinan Melih

doi:10.1016/j.engstruct.2011.05.024

Cited by 204 publications

(82 citation statements)

References 46 publications

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“…• Structure design optimization (Geem et al 2005b;Geem and Hwangbo 2006;Degertekin 2008Fesanghary et al , 2012Kaveh and Talataha 2009;Kaveh and Abadi 2010;Hasançebi et al 2010;Khajehzadeh et al 2011;Bekdas ß and Nigdeli 2011;Erdal et al 2011;Lagaros and Papadrakakis 2012;Kaveh and Ahangaran 2012;Shahrouzi and Sazjini 2012;Miguel and Miguel 2012;Lee and Geem 2004;Ryu et al 2007;Lee et al 2011). …”

Section: Discussionmentioning

confidence: 97%

Music Inspired Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

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In this chapter, we introduce a set of music inspired algorithms, namely, harmony search (HS), melody search (MeS) algorithm, and method of musical composition (MMC) algorithm. We first describe the general knowledge of harmony in Sect. 14.1. Then, the fundamentals and performances of HS, MeS algorithm, and MMC algorithm are introduced in Sects. 14.2 and 14.3, respectively. Finally, Sect. 14.4 summarises this chapter.

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Section: Discussionmentioning

confidence: 97%

Music Inspired Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

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“…In search of optimum mass, stiffness and damping coefficient of TMDs, HS based methodology was developed for the seismic structures [16,17]. Mass ratio factor and comparison of HS with closed form TMD formulas were done by Bekdaş and Nigdeli [18].…”

Section: Metaheuristic Algorithms In Tmd Optimizationmentioning

confidence: 99%

“…In the optimization of TMDs, different metaheuristic algorithms such as Particle Swarm Optimization (PSO) [8,9], Genetic Algorithm (GA) [10][11][12][13][14], Bionic Algorithm (BA) [15], Harmony Search (HS) [16][17][18][19][20], Ant Colony Optimization (ACO) [21], Artificial Bee Colony Optimization (ABC) [22] and Shuffled Complex Evolution (SCE) [23] have been employed. Generally, different design variables were optimized by considering different objectives depending to time domain or frequency domain responses.…”

Section: Metaheuristic Algorithms In Tmd Optimizationmentioning

confidence: 99%

Design of Tuned Mass Dampers via Harmony Search for Different Optimization Objectives of Structures

Niğdeli

Bekdaş

2015

Computational Methods in Applied Sciences

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In this chapter, an optimization methodology for tuning of tuned mass dampers (TMDs) on seismic structures was presented for two different objectives such as reducing the displacement of first story and absolute acceleration of top story of the structure. A metaheuristic method; harmony search (HS) was employed for optimization according to the time history analyses of structure under several earthquake excitations. Harmony search inspires musical performances in order to find optimum design variables according to optimization objective.Step by step, the methodology of the optimization process is explained in the chapter. The method was applied to find an optimum TMD for a seven story shear building and the optimum results were compared for the two cases considering displacement objective and acceleration objective. According to the results, optimum TMDs for both objectives are effective on both displacements and accelerations. But for acceleration objective, a small benefit for accelerations can be seen although the optimum mass of TMD is very heavy according to displacement objective.

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“…The spelling of Name for "Bektas and Nigdeli (2011)" has been changed to Bekdas and Nigdeli (2011) to match the entry in the reference list. Please confirm that this is correct and provide revisions if needed.…”

Section: Aq3mentioning

confidence: 99%

“…In recent years, several powerful metaheuristic optimization algorithms have been proposed and in the field of structural engineering their many successful applications have been reported in the literature. Metaheuristic methods such as genetic algorithm (GA), particle swarm optimization (PSO) (Gholizadeh 2013;Leung and Zhang 2009), ant colony optimization (ACO), simulated annealing, big bang-big crunch and harmony search (HS) (Bekdas and Nigdeli 2011;Fadel Miguel, Lopez, and Miguel 2013;Gholizadeh and Barzegar 2012) have been investigated to solve optimization problems. For optimization of passive dampers such as tuned mass damper (TMD) and viscous elastic damper (VED), metaheuristic methods have 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 2 M.N.S.…”

Section: Introductionmentioning

confidence: 99%

Investigating the optimal passive and active vibration controls of adjacent buildings based on performance indices using genetic algorithms

Hadi

2014

Engineering Optimization

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This study proposes the optimal passive and active damper parameters for achieving the best results in seismic response mitigation of coupled buildings connected to each other by dampers. The optimisation to minimise the H2 and H-norms in the performance indices is carried out by genetic algorithms (GAs). The final passive and active damper parameters are checked for adjacent buildings connected to each other under El Centro NS 1940 and Kobe NS 1995 excitations. Using real coded GA in H-norm, the optimal controller gain is obtained by different combinations of the measurement as the feedback for designing the control force between buildings. The propsed method is more effective than other metaheuristic methods and more feasible, although the contol force increased. The results ifn the active control system show that the response of adjacent buildings is reduced in an efficient manner. 1. Please check these proofs carefully. It is the responsibility of the corresponding author to check these and approve or amend them. A second proof is not normally provided. Taylor & Francis cannot be held responsible for uncorrected errors, even if introduced during the production process. Once your corrections have been added to the article, it will be considered ready for publication.Please limit changes at this stage to the correction of errors. You should not make insignificant changes, improve prose style, add new material, or delete existing material at this stage. Making a large number of small, non-essential corrections can lead to errors being introduced. We therefore reserve the right not to make such corrections.For detailed guidance on how to check your proofs, please see http://journalauthors.tandf.co.uk/production/checkingproofs.asp. The reference "Hadi and Arfiadi (2011)" is cited in the text but is not listed in the reference list. Please either delete in-text citation or provide full reference details following journal style. Please review the AQ3The spelling of Name for "Bektas and Nigdeli (2011)" has been changed to Bekdas and Nigdeli (2011) to match the entry in the reference list. Please confirm that this is correct and provide revisions if needed. AQ4The reference "Pourzeynali et al. (2006)" is cited in Tables 8 and 9 but is not listed in the reference list. Please either delete in-text citation or provide full reference details following journal style. How to make corrections to your proofs using Adobe AcrobatTaylor & Francis now offer you a choice of options to help you make corrections to your proofs. Your PDF proof file has been enabled so that you can edit the proof directly using Adobe Acrobat. This is the simplest and best way for you to ensure that your corrections will be incorporated. If you wish to do this, please follow these instructions:1. Save the file to your hard disk.2. Check which version of Adobe Acrobat you have on your computer. You can do this by clicking on the "Help" tab, and then "About."If Adobe Reader is not installed, you can get the latest version free from http://get.a...

show abstract

Estimating optimum parameters of tuned mass dampers using harmony search

Cited by 204 publications

References 46 publications

Music Inspired Algorithms

Music Inspired Algorithms

Design of Tuned Mass Dampers via Harmony Search for Different Optimization Objectives of Structures

Investigating the optimal passive and active vibration controls of adjacent buildings based on performance indices using genetic algorithms

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