Journal
ENGINEERING OPTIMIZATION
Volume 48, Issue 11, Pages 1990-2006Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/0305215X.2016.1150468
Keywords
modified subpopulation teaching-learning-based optimization (MS-TLBO); truss topology optimization (TTO); mass optimization; static and dynamic constraints
Ask authors/readers for more resources
In this study, an improved version of the teaching-learning-based optimization (TLBO) algorithm is proposed for truss topology optimization (TTO), with static and dynamic constraints on planar and space trusses. The basic TLBO algorithm is improved to enhance its exploration and exploitation abilities by considering various factors such as the number of teachers, adaptive teaching, tutorial learning and self-motivated learning. The TTO problems are considered with multiple load conditions and subjected to constraints for natural frequencies, element stresses, nodal displacements, Euler buckling criteria and kinematic stability conditions. TTO is achieved with the removal of superfluous elements and nodes from the ground structure, and results in a mass saving. In this method, difficulties arise owing to singular solution and unnecessary analysis; therefore, the finite element model is reformed to resolve these issues. A single-stage optimization approach is used,in which size and topology optimization are considered simultaneously. The results obtained are compared with the best solutions obtained by the algorithm. The results reveal that the modified subpopulation teaching-learning-based optimization(MS-TLBO) algorithm is more effective thanother state-of-the-art algorithms.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available