Configuration design of structures under dynamic constraints by a hybrid bat algorithm and teaching–learning based optimization

Optimal design of steel trusses is an interesting task due to existence of many alternatives for their spatial configuration. Meanwhile, performance criteria have enforced their vibration to maintain within certain limits. The present work concerns implementation of frequency constraints as a common...

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Bibliographic Details
Published in:International journal of dynamics and control Vol. 7; no. 2; pp. 419 - 429
Main Authors: Shahrouzi, Mohsen, Rafiee-Alavijeh, Fataneh, Aghabaglou, Mahdi
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2019
Springer Nature B.V
Subjects:
Algorithms
Bridges
Complexity
Computer simulation
Configuration management
Configurations
Control
Control and Systems Theory
Design optimization
Dynamical Systems
Engineering
Machine learning
Search engines
Trusses
Vibration
Frequency constraint
Geometry optimization
Eigenvalue analysis
Hybrid meta-heuristic
ISSN:2195-268X, 2195-2698
Online Access:Get full text
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Summary:Optimal design of steel trusses is an interesting task due to existence of many alternatives for their spatial configuration. Meanwhile, performance criteria have enforced their vibration to maintain within certain limits. The present work concerns implementation of frequency constraints as a common approach to implicitly satisfy such practical requirements. The problem objective is to minimize the cost of steel material by simultaneous size and geometry optimization of trusses. In this regard teaching – learning - based - optimization and bat - algorithm are hybridized via a new effective framework. The former acts as a global search engine, the latter provides search refinement to access higher quality solutions. Effectiveness and efficiency of the proposed hybrid method are evaluated using a number of bridge and space structures via comparison with literature works. Numerical simulations show enhanced effectiveness and less deviation about final optimum design as a result of implementing the proposed hybridization.
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ISSN:2195-268X
2195-2698
DOI:10.1007/s40435-018-0455-6